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A Case Study On: The Return of Inflation

• January 14, 2021

After a forty-year bond market rally from a high of 18% in 1982 to the current 0.70% low today, we struggle to get excited about bonds in the short or medium term.

Now What to Do?

Bonds have always been there to diversify from the volatility of the stock market.  The idea was, and is, when stocks go down, bonds go up, and vice versa.  In 2020, we saw that historical relationship break.  When stock markets crashed in March, the Bond Market went down as well until the Federal Reserve and Bank of Canada “saved” the Bond Market.

Another attribute is that bonds are there for capital preservation despite having little yield, which is a very important attribute to have when dealing with risk or asset allocation of clients’ wealth.

When we look beyond those two benefits, we struggle to find many opportunities in the credit or interest rate market due to historically low interest rates. As well, we have seen the central banks’ interventions into the credit markets suppress credit spreads.

Where Do the $300 Trillion in Global Debt Markets Go From Here?

For the past two decades, analysts, economists and central banks have forecasted incorrectly that global bond yields should yield at higher levels. The ongoing combination of technological disruption, global free trade expansion and our aging population has caused deflationary pressure, therefore causing yields to be suppressed.

Why It’s Different This Time

For the past decade, central banks have “pumped” the system with a massive injection of money for two reasons.  Firstly, for the public markets to function properly.  Secondly, they are trying to keep businesses afloat (large and small).  The former worked wonderfully, the latter not so much.

When central banks increase liquidity, they release funds to the banking sector. The problem has been that this money doesn’t leave the bank and get lent out into the economy. The banks are too scared to lend or it is too expensive (from a capital perspective) for them to lend. So, the money never gets into the hands of main street and the commercial banks just buy government bonds to keep on their balance sheets.

For the economy to recover, the commercial banks need to get money into people’s hands. This could happen.   More on that later .

The Central Banks are also trying to reflate the economy. To get inflation, you need several conditions in place.  Or to say it differently, you need specific ingredients to bake an inflation cake:

1. Central Banks Are Slowly Losing Their Independence

With record amounts of sovereign debt, there is very little chance that central banks will not be influenced politically. There is a view that the only way out is to inflate the debt away.  This occurred in 1948.  After WWII, the Allied countries were left with a massive amount of debt.  They had little chance of paying it back.  So, they used inflation as a monetary trick.  After the war, there was tremendous pent-up demand resulting from rationing, consumer high savings rates and European rebuilding (Marshall Plan). All this caused inflation over several years. They used higher inflation to lower the outstanding debt since future dollars are worth less than present dollars, thereby dropping the real debt ratios.

2. Labour Market and Class Division

There will be a new agenda focusing on closing the divide between the upper class and the middle class.  We have started to see wage increases. As an example, minimum wage workers have seen their wages double. We believe we are going to hear more of new labour union creation for the working class to extract more profits from their companies. An example is the organizing of Amazon workers.

3. Global Trade

A) modern trade agreements and reshoring.

We have seen so much deflation coming from global trade agreements set in the 1990s and 2000s. The Agreements in place are starting to unwind.  We are seeing western countries renegotiate trade deals that encompass not only economic benefits but must have social benefits as well, which will lead to higher prices for goods.  Manufacturing is also looking to bring back their production to their own country, which is called reshoring. Goods will be more expensive.

b) Cold Trade War with China

Western economies are starting to re-evaluate their relationship with China due to trust issues. Cybersecurity, political intervention by the Chinese state and uneven access to their markets is causing the West to re-evaluate our relationship.  This will mean that companies will try to find other options such as reshoring manufacturing.  This will lead to higher prices.

4. ESG (Environmental Social Governance), Social Lending, Justice and Green Programs

This type of policy is now in vogue. Even though it is just and honourable to consider these social lending polices, from an economic perspective the policies will force higher prices since these policies have a cost which must be shared throughout society.

5. Central Banks’ Policies Mandate Inflation

Most central banks have abandoned low inflation policy.  The US Federal Reserve has now installed a policy where inflation targets should be at minimum 2%.  Central banks have said they will not tighten monetary policy until they see a complete recovery.

6. Asset Prices Are Now Inflationary

Whether it is housing, the stock market or bitcoin, all asset classes are now reaching bubbling levels that will trickle down into the Consumer Price Index (CPI) inflation calculation.

7. Interest Rate Curve Suppression ( Not Happened Yet )

There has been recent discussion on central banks trying to control and pin down long-term interest rates by purchasing unlimited amounts of bonds to keep the interest rate curve low. If this does happen, inflation will certainly rise.

8. Macro Prudential Regulation ( Not Happened Yet )

As previously mentioned, central banks will be pressured politically.  The main issue is that money expansion is not getting to the consumer or small business. There is early talk that governments could force banks to lend by guaranteeing all loans to their customers.  Or governments could force their central banks to buy outstanding federal debt, thereby creating money by fiat.  (Most modern currencies are fiat or paper currencies that are not based on a commodity such as gold.) Regardless, if this does happen, inflation becomes a real issue.

We do believe reflation is on the horizon.  We believe that inflation will easily move from 1.5% to potentially 3.0% in six months. Over time, we think that higher inflation is a bigger risk than lower inflation. If that occurs, it is a headwind for the bond portfolio.

With this in mind, we have been in a defensive mode since mid-2020 with our bond portfolio by doing the following:

• Lower term-to-maturity (shorter duration):  3.5 years versus 7 years for the index
• Credit exposure primarily in the 1 to 3 year area
• Larger weight towards REITs – sector trades at a discount to its Net Asset Value
• Lower weight to High Yield – sector shows little value versus risk.
• Possible purchase of inflation index-linked bonds in near future.

(As a reminder we can own 20% of the bond portfolio in higher risk assets such as convertibles, real estate investment trusts, preferred shares, and non-investment grade bonds.)

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Case Study: Should a Dollar Store Raise Prices to Keep Up with Inflation?

• Marco Bertini

A discount retailer that’s struggling to maintain margins needs a new strategy.

Discount retailer Dollar Bill’s has been struggling to maintain its margins over the past two years because of inflationary pressures, delays on imported goods, and decreased foot traffic. Now the board has asked CEO William Fisher Jr. to develop a strategy for raising prices. William worries that raising prices will hurt the company’s reputation and alienate customers, but he recognizes that something has to change.

Should Dollar Bill’s maintain the dollar price point by reducing product quantity, such as repackaging five-packs of chewing gum into four-packs for the same price? Or should it abandon the dollar price point and begin offering an array of more-expensive goods? This fictional case study features expert commentary by Greg Besner, the CEO of Sunflow, and Barrie Carmel, the vice president of pricing at Michaels Stores.

William Fisher Jr. opened the door to his office and pointed to the metal folding table in the corner. It was the one his father had bought in 1957, the year he founded Dollar Bill’s, and staffers now jokingly—but lovingly—referred to it as “the executive conference table.” Today it was covered with packs of candy, stationery items, bottles of water, tiny action figures, and countless other knickknacks.

• Jill Avery is a senior lecturer of business administration and the C. Roland Christensen Distinguished Management Educator in the marketing unit at Harvard Business School.
• Marco Bertini is a professor in marketing at Esade, Universitat Ramon Llull, in Barcelona. He is also senior adviser to Globalpraxis, a consultancy specialized in accelerating organic growth.

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Money supply, inflation and output: an empirically comparative analysis for Vietnam and China

Asian Journal of Economics and Banking

ISSN : 2615-9821

Article publication date: 11 October 2021

This study focuses on analyzing the relation between money supply, inflation and output in Vietnam and China.

Design/methodology/approach

Using the error correction model and the vector autoregression model (ECM and VAR) and the canonical cointegration regression (CCR), the study shows similar patterns of these variable relations between the two economies.

The study points out the difference in the estimated coefficients between the two countries with different economic scales. While inflation in Vietnam is strongly influenced by expected inflation and output growth, inflation in China is strongly influenced by money supply growth and output growth.

Originality/value

To the best of the authors’ knowledge, this is the first empirical and comparative research on the relation between money supply, inflation and output for Vietnam and China. The study demonstrates that the relationship between money supply, inflation and output is still true in case of transition economies.

• Money supply
• Monetary policy

Long, P.D. , Hien, B.Q. and Ngoc, P.T.B. (2021), "Money supply, inflation and output: an empirically comparative analysis for Vietnam and China", Asian Journal of Economics and Banking , Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/AJEB-03-2021-0040

Emerald Publishing Limited

Copyright © 2021, Pham Dinh Long, Bui Quang Hien and Pham Thi Bich Ngoc

Published in Asian Journal of Economics and Banking . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

1. Introduction

During economic transition, China has been considered a leader among socialist countries that have successfully transformed the economic model from a planned economy to a market-oriented economy. Economic reform is urgent and under pressure when the economy suffers serious crises. This reform is similar in Vietnam, but Vietnamese reform is 10 years later than Chinese one (1978 in China, 1986 in Vietnam) ( Ma, 1999 ; Dao and Vu, 2008 ). It can be said that economic reform in China has provided some experience and creates motivation for many countries to conduct similar transitions. However, China and Vietnam are the only two countries that have been transformed from a planned economy to a market-oriented economy while keeping their own orientations. In the 1980s, apart from changing the political system, the Soviet Union and Eastern European countries have shifted to the market economy. In the area of monetary policy, China and Vietnam also have a thorough transition from one-tier bank system – which holds full control of the national financial system to two-tier bank system – by splitting into central banks and commercial banks, providing credit services for specific industries ( Ma, 1999 ; Oanh, 2001 ; Dao and Vu, 2008 ). This change helps the instruments of monetary policy be activated and gradually take effect. Monetary turmoil phenomena created by mixed economies (systems including a planned economy and a market economy at the same time) have narrowed. Inflation is lowered and controlled to be more stable than before reform. Capital markets were formed after nearly a decade of economic reform (1990 in China, 2000 in Vietnam). On the other hand, Vietnam's accession to the World Trade Organization is 6 years later than China (China in 2001, Vietnam in 2007). These show that China always implements important steps in reform and achieves results before Vietnam.

There are similarities as well as differences in the economy between Vietnam and China ( Duong and Le, 2007 ). Both countries pursue the market-oriented economy, the same pattern of economic reform, development and integration process. Particularly, Vietnam follows the socialist-oriented market economy. China follows a “socialist market economy with Chinese characteristics. The political systems of two countries have certain similarities. Similarities may come from the success of China's economic reform policies, and these policies are always ahead of Vietnam ( Ma, 1999 ; Dao and Vu, 2008 ). Moreover, in terms of economics, if a country accepts and operates under a market mechanism, relations in that economy will also have to follow the rules of the market. This leads to similarities in results. However, the size of two economies is different. The capacity of influence on economics and politics is also different ( Duong and Le, 2007 ; VNEP, 2016 ). Furthermore, in terms of geography and history, China is less influenced by political and economic changes in the world than Vietnam. In fact, China is an important element which contributes to the establishment of international relations in general and in the economic field in particular. In the opposite direction, Vietnam is strongly affected by these relations.

In the quantity theory of money (QTM), the relation between money stock ( M ) and price level ( P ) can be expressed through the equation M V = P Y ( Mankiw, 2016 ) where M is the money supply, V is the velocity of circulation of money, Y is the real output and PY is the nominal output. The velocity of circulation of money is defined as the average amount of one unit of money circulated in the economy to pay for goods and services during a given period of time. Gross domestic product (GDP) is chosen as the variable representing the output, and P is chosen as the deflator (GDP deflator). According to Chow and Shen (2005) mentioned the work of Friedman, there are limitations in the equation M V = P Y because in practice this relation is not really accurate. In the equation, with Y held constant, P tends to increase as M increases; with M held constant, P tends to increase as Y decreases and with P held constant, Y tends to increase as M increases. In the long run, the QTM is limited for several reasons. First, interest rate affects V , and this effect may not be constant in the long run. Second, the equation mentioned can be transformed into M / P = Y / V . This equation describes a demand for money equation responding to changes in income. In fact, the demand for money equation is influenced not only by income but also by interest rate and other factors ( m − p ) = f ( S , O C ) where ( m − p ) denotes the real money demand and S , O C represents variables that show opportunity costs of holding money.

This study focuses on analyzing the relation of three macro-variables, including money supply real output and price level. Although this issue seems to be simple and obvious, previous studies about it are only conducted in other countries and China but not Vietnam ( Chow and Shen, 2005 ; Aksoy and Piskorski, 2006 ; Budina et al. , 2006 ; Homaifar and Zhang, 2008 ; Haug and Dewald, 2010 ; Anh and Thuy, 2013 ; Truong, 2013 ). In addition, limited data can be a reason why empirical research on this issue has not performed in Vietnam in previous studies. What is the relation between these three variables when two countries have many similarities in terms of economics and politics but have different economic scales? This paper will examine the relationship between money supply, inflation and output in Vietnam during the period 1986–2016 and in China during the period 1978–2008. After 30 years of reform, the study aims to demonstrate the existence of the relation between these variables and expect a new finding when using new quantitative techniques in time series data processing. Accordingly, the study contributes to shed light on the interaction between variables mentioned in the area of monetary policy management.

The paper is organized as follows. Section 1 highlights briefly the achievement of economic reform as well as the similarities and differences in the economy between Vietnam and China. This section also mentions the QTM, M V = P Y and its limitation. Section 2 presents the methodology in the error correction model (ECM) following vector autoregression model (VAR) structure and canonical cointegration regression (CCR) for the multivariate variable. From this, the model specifications and data source are described in Vietnam and China case studies. The result of empirical study is presented in Section 3 , which discusses the outcomes. One interesting result is that the different parameters of estimation between two countries are with different economic scales. In Vietnam, the expected inflation and output growth have a strong impact on inflation. In contrast, the inflation in China is strongly affected by money supply growth and output growth. Another noteworthy thing is that the increasing money supply to stimulate investment and boost economic growth in Vietnam is less effective than in China. In addition, the impact of income on money demand in Vietnam is much lesser than in Vietnam. The conclusion is shown in Section 4 , which emphasizes some remarkable findings.

2. Methodology

2.1 research model.

Based on the equation M V = P Y , the study proposes models with variables that can interact with each other. The error correction model and the vector autoregression model (ECM-VAR) are used, and then canonical cointegration regression (CCR) is applied with an expectation that regression results are reliable when the phenomenon of serial correlation and endogeneity is adjusted. (1) [ Δ ⁡ log ( P t ) Δ ⁡ log ( Y t ) Δ ⁡ log ( M 2 t ) ] = [ a 1 a 2 a 3 ] [ Δ ⁡ log ( P t − 1 ) Δ ⁡ log ( Y t − 1 ) Δ ⁡ log ( M 2 t − 1 ) ] + [ b 1 b 2 b 3 ]

2.2 Data research

In Vietnam, data are collected from 1986 to 2016 from the World Bank (WB), the International Monetary Fund (IMF), the State Bank of Vietnam (SBV) and Asset Macro in the UK ( http://assetmacro.com ). GDP and consumer price index (CPI) are chosen as variables representing the output variable (symbol Y ) and the price variable (symbol P ). GDP is collected directly from World Development Indicators (WDI) of WB with the original price in the base year 2010. The CPI is taken from the IMF with the comparative price of 2010 for the period 1995–2016. For the period 1986–1994, the CPI is collected from the IMF with the comparative price of 2005 and transferred to the original price of 2010 by applying the author's formula (3) . Y and M 2 variables are valued variables. The CPI variable is in percentage form. M 2 money supply is collected from the IMF, SBV and Asset Macro with comparison.

In China, variables including M 2 money supply, the retail price index and GDP are used to represent money supply M 2, price level P and output Y . The data are derived from the study of Chow and Shen (2005) for the period 1952–2002 and from China Statistical Yearbook of the National Bureau of Statistics (NBS) of China for the period 2003–2008. The data for the period 1952–2002 are taken from the NBS, but estimates are similar to the methods that the author used when the data are not directly available (see data description of Chow and Shen (2005) ). (2) C P I ( t ) s s 2010 = C P I ( t ) s s 2005 C P I ( 2010 ) s s 2005 × 100

3. Empirical result

3.1 unit root test and johansen cointegration test.

The study uses unit root test to test the stationary of variables, for the case of Vietnam (1986–2016) and China (1978–2008). At the first difference, results show that the null hypothesis of a unit root for all variables considered can be rejected. This means that variables stop at the first difference ( Table 1 ). After testing for stationary, Johansen cointegration test is conducted. A value of 1% (or 5%) is greater than the value of trace statistics for both Vietnam and China ( Tables 2 and 3 ). Results indicate that there exists a long-term relationship between variables log ( M 2 t ) , log ( P t ) , log ( Y t ) . This is the basis for further analysis.

3.2 Volatility of price level and inflation

The equation M V = P Y can be rewritten as the formula P = V ( M / Y ) . Accordingly, the price level P is influenced by two factors, namely money supply and output. M variable is M 2, and Y variable is the real GDP. M 2 money supply is chosen because interest rate may have a stronger impact on M 1 money demand than M 2 money demand. Increasing in interest rate will make M 1 money demand be likely to decrease due to the relationship with the profitability of deposit. In the case of Vietnam, Figure 1 shows that log ( P ) has a long-term positive relationship with log ( M / Y ) and has a nearly linear relation. The price level P is the consumer price index in Vietnam with the base year 2010. In the case of China, although the starting point of the curve in Figure 2 is different from Vietnam, the positive relationship between the price level P and M 2/ Y is still quite obvious. The price level P is the retail price index of the base year 1978 and is selected similarly to the research of Chow and Shen (2005) . (3) log ( P ) = 4.8306 + 0.6302 ⁡ log ( M 2 / Y ) (4) log ( P ) = − 0.9342 + 0.4182 ⁡ log ( M 2 / Y )

OLS regression results which show the impact of M 2/ Y on the level price P are presented in equations (3) and (4) , respectively, for Vietnam in the period 1986–2016 and for China in the period 1978–2008 after 30 years of reform ( Table 4 ). The estimated coefficients show no big significant difference between the period 1952–2002 and the period 1978–2008. Specifically, the elasticity of log ( P2 ) is 0.374 in the period 1952–2002 ( Chow and Shen, 2005 ) and 0.418 in the period 1978–2008. In Vietnam, the elasticity (0.630) of log ( M2 / P ) against log ( P ) is larger than that of China but not so different. Lag 1 of the residuals of the corresponding OLS model is saved as an independent variable. This variable is used to represent the adjustment coefficient in the ECM-VAR for the inflation estimation model Δ ⁡ log ( P ) . The regression results are rewritten as formulas (5) and (6) for Vietnam and China, respectively, with the same data length as in the Ordinary Least Squares (OLS) model. There are similarities in the regression results for both Vietnamese and Chinese economies. Results in Table 5 show the inflation in year  t in Vietnam and China affected by last year's inflation and the corresponding increase in money supply in the year studying. However, the increase of money supply in the previous year does not suggest any impact on the current year's inflation. According to the Fisher's QTM, price level changes are based on changes in the quantity of money. Changes in the price level P and changes in money supply are proportional. However, in fact, there is an impact lag between the time a policy is enacted and the time such policy influences the economy under changes in the economic situations. The formula does not mention the period of time required from the moment the central bank begins to implement the monetary policy instruments that affect macroeconomic factors in the economy. The study of Chen (2006) on the relation between the lag of money supply and inflation for Chinese economy indicates that inflation is affected by money supply with at least a five-month lag. Because the model is estimated by year, the increase in money supply will affect inflation in that year. The study of Chow and Shen (2005) , which estimates inflation for Chinese economy during the period 1952–2002, also reaches the same conclusion. However, there is a difference in the adjustment coefficient towards the equilibrium in these two countries. In Vietnam, the adjustment coefficient of the ECM model is negative and not statistically significant. This suggests that the model, in the long run, is not self-adjusting to the equilibrium. Meanwhile, inflation estimation for Chinese economy indicates that in the long run, the model can be adjusted to the equilibrium with the adjustment factor of −0.223 at a 1% significance level. The regression shows no big difference between China and Vietnam when considering the effect of last year's inflation on current inflation. Specifically, the elasticities are 0.558 and 0.656 in China for the period 1952–2002 ( Chow and Shen, 2005 ) and the period 1978–2008, respectively. In Vietnam, both estimated coefficients are not significantly different from each other (0.439) compared to the case of China. However, there are differences in the impact on inflation in these two countries when assessing the impact factors (0.617 is much higher than 0.216). This shows that inflation in Vietnam reacts more strongly to changes in the monetary policy than in China. (5) Δ ⁡ log ( P ) t = − 0.0145 + 0.6168 Δ ⁡ log ( M 2 / Y ) t + 0.4392 Δ ⁡ log ( P ) t − 1 − 0.2253 Δ ⁡ log ( M 2 / Y ) t − 1 − 0.0732 u t − 1 (6) Δ ⁡ log ( P ) t = − 0.0012 + 0.2164 Δ ⁡ log ( M 2 / Y ) t + 0.6556 Δ ⁡ log ( P ) t − 1 − 0.0629 Δ ⁡ log ( M 2 / Y ) t − 1 − 0.223 u t − 1

3.3 Money supply, inflation and output

The relation between money supply, inflation and output are regressed by the ECM-VAR model. Tables 6 and 7 show the comparison of regression results for money supply, inflation and output in Vietnam during the period 1986–2016 and in China during the period 1978–2008 after 30 years of reform and the period 1952–2002 according to the research of Chow and Shen (2005) . The results of the ECM-VAR model show that there is a downside when some important impacts are not statistically significant, and expected signs are different from expectation. For example, the impact of money supply on growth is not statistically significant for both Vietnam and China. Money supply and growth which have negative impacts on inflation are statistically significant at 5 and 10%, respectively in the case of Vietnam. Results of the autocorrelation test and the normality test of residuals are violated in some cases. In Vietnam, there is an autocorrelation phenomenon when considering LM(2) at a significance level of 5%. The residuals are not normally distributed when Δ ⁡ log ( P t ) is a dependent variable at a 5% significance level. In China for the period 1952–2002, autocorrelation occurs in LM(1) at the significance level of 1%, and the residuals are not normally distributed at a significance level of 5% when Δ ⁡ log ( P t ) and Δ ⁡ log ( Y t ) are considered dependent variables. For the period 1978–2008 (30 years after reform), results show that the residuals are normally distributed, and there is no autocorrelation in the model. However, the number of variables that have statistical significance is not like what expected. For example, while it is often discussed in the monetary policy that an increase in money supply brings upward pressure on inflation ( Friedman, 1970 ), there is no such evidence of ECM outcomes. The study continues to run the CCR model with an expectation that regression results are reliable when the phenomenon of serial correlation and endogeneity is adjusted ( Wang and Wu, 2012 ). The regression results suggest that there is a similarity in the relation between the above mentioned three variables for both economies. The interaction is consistent with the QTM. An increase in money supply leads to an increase in inflation and promotes growth. Inflation and growth have impacts on inflation and growth in the future. Money demand is affected by income. The results of the CCR model are shown in Table 8 .

In terms of inflation, all variables, including M 2 money supply growth, inflation and output growth, in the previous year influence inflation in the current year in both cases of Vietnam and China. First, the regression results show that inflation in Vietnam is strongly affected by inflation in the previous year. If inflation in the previous year is on an upward trend, it is likely that inflation in the following year will increase. On the other hand, due to a time lag in monetary policy implementation, inflation is difficult to control and may reverse in the next year. For the Chinese economy, last year's inflation also affects inflation in the current year, but this effect is weaker than that in Vietnam (0.180 < 0.381). This suggests that using the lagged value of inflation as expected inflation is inadequate since the estimated coefficient of Vietnam is almost two times higher than that of China. Second, output growth in the previous year increases pressure on inflation in the current year. This effect can be explained by the aggregate supply-aggregate demand model (AS-AD). When the economy has not reached potential output, an increase in the level of output will lead to an increase in the price level. The impact factor of output growth on inflation in Vietnam is approximately two times smaller than that of China (0.332 < 0.657). This implies that growth in Vietnam just partly influences inflation. Meanwhile, growth seems to have a huge impact on inflation in China. Third, a rise in M 2 money supply growth in the previous year exerts upward pressure on the current year's inflation. In the money market, an increase in money supply will lead to a decrease in the base rate. Reduced interest rate helps stimulate investment and contribute to a rise in the aggregate demand. In the AS-AD model, an increase in the aggregate demand results in an increase in the price leve,l which in turn raises inflation. Moreover, this is consistent with Friedman's finding in which inflation is a monetary phenomenon that happens when the quantity of money increases more rapidly than output ( Friedman, 1970 ). There is a difference in the regression results for Vietnam and China. In Vietnam, the effect of Δ ⁡ log ( M 2 t − 1 ) on Δ ⁡ log ( P t ) (0.137) is smaller than the effect of Δ ⁡ log ( P t − 1 ) on Δ ⁡ log ( P t ) (0.381). In contrast, in China, the effect of Δ ⁡ log ( M 2 t − 1 ) on Δ ⁡ log ( P t ) (0.330) is greater than the effect of Δ ⁡ log ( P t − 1 ) on Δ ⁡ log ( P t ) (0.180). This interesting result shows that while money supply shocks influence inflation in Vietnam, there exist other factors that have strong impacts on inflation. Studies suggest that this result is appropriate for developing countries, like Vietnam. The regression results show that other effects come from expected inflation. In Vietnam, inflation is often volatile and sometimes the evolution of annual inflation is far away from inflation targeting ( Do and Huong, 2014 ). This creates a psychological fear that inflation in the past will not be adjusted soon, continue to maintain and even increase in the next year. On the other hand, Vietnam has a relatively large open economy ( VNEP, 2016 ). Inflation is not only affected by the implementation of fiscal and monetary policy and internal macroeconomic variables inside the economy but also external factors. External factors may be the exchange rate of dong against other currencies, world economic crises, political instability, etc. For instance, when China devalue its currency to boost exports, Vietnam also has to devalue the dong (VND) to increase the competitiveness of its exports. Meanwhile, the cost of domestic production increases due to a rise in the price of inputs. Currency devaluation can lead to an increase in domestic production costs. This can raise inflation. At the same time, forecasting scenarios and macroeconomic policies are difficult to anticipate. In the opposite direction, China is the second largest economy in the world. China's inflation is less affected by other factors than small economies' inflation. Obviously, if Vietnam devalues its currency first, it is unlikely that this will affect other major countries or make them reconsider their macroeconomic policies.

In terms of output, output growth is positively affected by M 2 money supply growth and output growth in the previous year and is negatively affected by last year's inflation. First, results show that increasing money supply to stimulate investment and boost growth in Vietnam is less effective than in China (0.0296 > 0.378). This implies that the quantity of money injected into the economy to use for investment growth is restricted, or investment efficiency is not high. Second, the negative impact of inflation and the positive impact of M 2 money supply growth in the previous year are very small in the case of Vietnam. Meanwhile, the regression results for China show that the signs of these two estimated coefficients are similar to those for Vietnam, but the impact is high. Previous studies suggest that inflation has a negative impact on growth ( Ghosh and Phillips, 1998 ; Dammak and Helali, 2017 ). In Vietnam, the elasticity of expected inflation on output growth is low. According to the regression results, this may be due to the strong impact of the expected output growth (0.533) and the impact of other factors other than money supply and inflation. Third, there is a similarity in the impact factor of the expected output growth on output growth for both Vietnam (0.533) and China (0.537).

4. Conclusion

After 30 years of reform, both Vietnam and China have made a successful revolution from a planned economy to a market economy, creating tremendous economic development. Through empirical evidence, the study demonstrates that the relationship between money supply, inflation and output is still true in the case of transition economies. The law of the market is correct, though the orientation of certain market economies is different from that of developed countries with a long-standing market economy. In addition, the study shows that the degree of the interaction between money supply, inflation and output varies responding to particular conditions of two countries, in which both pursue a market-oriented mechanism but differ in the scale of the economy.

Plotting log( P ) against log( M 2/ Y ) for Vietnamese economy in the period 1986–2016

Plotting log( P ) against log( M 2/ Y ) for Chinese economy in the period 1978–2008

Results of unit root test

Note(s): * 1 , * 5 , and * 10 denote the significance at the 1%, 5%, and 10% levels, respectively

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Acknowledgements

Funding: This research is funded by Vietnam National Foundation for Science and Technology Development (NAFODSTED) under grant number 502.01-2018.316.

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• Original Article
• Published: 04 May 2021

Empirical analysis of the relationship between openness and inflation: a case study of sub-Saharan Africa

• Francis Obeng Afari   ORCID: orcid.org/0000-0003-0744-9161 1 ,
• Jong Chil Son 1 &
• Horlali Yaw Haligah 2  

SN Business & Economics volume  1 , Article number:  72 ( 2021 ) Cite this article

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Earlier empirical studies carried out on the relationship between openness and inflation have focused mainly on long run effects without considering the short run dynamics. However, this study looked at both the short run and long run relationship between openness and inflation for 25 countries in Sub-Saharan Africa (SSA) using an annual data spanning from 1985 to 2017. The Autoregressive Distributed Lag (ARDL) Model and the Dumitrescu Hurlin panel causality test were the main estimation techniques employed by this study. The results revealed a significant positive relationship between trade openness and inflation both in the short run and long run. Also, there was an evidence of positive relationship between financial openness and inflation both in the short run and long run. However, the relationship was statistically insignificant in the short run. The study further showed a bidirectional relationship between trade openness and inflation, at least for a 9-year lag period. These findings highlight the role openness play in affecting price levels in SSA. Hence, the study recommends that policy makers and various governments in SSA need to design and execute programmes that would help build import substitution industries. Also, government must strengthen the financial sector and increase its supervisory role by ensuring that laws are strictly adhered to by all financial actors. This will help curtail the problem of money laundry in the sub-region thereby reducing the adverse effects opening up the financial sector has on price levels.

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Afari, F.O., Son, J.C. & Haligah, H.Y. Empirical analysis of the relationship between openness and inflation: a case study of sub-Saharan Africa. SN Bus Econ 1 , 72 (2021). https://doi.org/10.1007/s43546-021-00081-6

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The impact of macroeconomic factors on food price inflation: an evidence from India

• Asharani Samal   ORCID: orcid.org/0000-0001-8275-0267 1 ,
• Mallesh Ummalla 2 &
• Phanindra Goyari 1  

Future Business Journal volume  8 , Article number:  15 ( 2022 ) Cite this article

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The present study investigates the impact of macroeconomic factors on food price inflation in India utilizing the monthly time series during January 2006–March 2019. The long-run relationship is confirmed among the variables using the ARDL bounds testing approach to cointegration. The coefficients of long-run estimates show that per capita income, money supply, global food prices, and agricultural wages are positively and significantly impacted food price inflation in both the short and long-run. While food grain availability has a negative and significant impact on food price inflation in both the short-run and long run. Further, the short-run estimates revealed that real exchange rate positively impacts food price inflation. However, the coefficient is insignificant in the short-run. The Granger causality estimates show that a short-run bidirectional causality is confirmed among per capita income, the exchange rate, per capita net availability of food grain and food price inflation. Further, there is evidence of unidirectional causality running from global food prices to food price inflation. However, there is no causal relationship running from money supply and agricultural wages to food price inflation in the short-run.

Introduction

The main objective of monetary policy in any economy is to maintain price stability. However, high food price inflation affects not only macroeconomic stability but also small farmers and poor consumers of the developing country where poor people spend their massive portion of income on food consumption. Agricultural commodity price volatility negatively impacts all societies by causing macroeconomic instability; specifically, it affects the impoverished that spend a large portion of their resources on food and fuel [ 47 ]. Therefore, high food price inflation has become a significant concern among the researchers and policymakers in determining responsible factors to surge in food price inflation. The high food price inflation has been experienced in the recent period due to increasing demand for biofuels in many developed countries, increasing demand for various diets among newly prosperous populations as compared to the production of such foodstuff, rise in minimum support prices, rapid regional economic growth, increasing the cost of fertilizers and other inputs, rising oil prices, etc.

Agriculture is very competitive in producing homogenous goods, given its vulnerability and high dependence on monsoon. It also contributes 17% of gross domestic product and employs more than 50% of the population. However, the contribution of the agricultural sector to GDP has been declining substantially since 2014, and the growth of agriculture is likely to increase by 2.1% in 2018–19 [ 23 ]. Further, price of agricultural products is more volatile than the non-agricultural sector due to high dependence on climate change. Therefore, attention should be given to the agricultural sector and the behavior of agriculture prices, especially for developing countries like India, where the majority of the population depends on agriculture. The persistent and high food price inflation over the period has gained more extensive attention in India by the researchers and policymakers as food price inflation has been the major contributor behind the increase in overall Wholesale Price Index (WPI) inflation in India [ 2 ]. Further, agricultural price is susceptible to relative changes in input prices, supply factors, etc.

Theoretically, rising food prices are basically due to two factors in the literature, i.e., real and monetary shocks. These are explained by structuralist and monetarist approaches, respectively. According to structuralists, the money supply is passive, and the real shocks in a particular sector tend to upsurge in food price inflation. Hence, inflation occurs in the prices of other goods. However, monetarists argued that inflation could arise through an autonomous increase in money supply via generating aggregate demand, which increases the relative price of commodities. Therefore, an increase in money supply is a cause for inflation, not necessarily by real shocks.

However, the developing countries like India are not exceptional from higher food prices and macro-economic instability. Since the 1991 economic reforms, the Indian economy has maintained a single-digit economic growth rate and moderate inflation. However, in recent years, one of the major problems that the Indian economy is facing is higher food price inflation. The WPI food price inflation was documented 10.20% during January 2008–July 2010 [ 33 ]. Further, CPI-IW for food was experienced at 8.05% during 2006–2019 while it was recorded at 13%, especially in 2013. However, the growth rate of gross food grain production was 2.66% during this period. The demand for food commodities increases at a higher rate due to the high economic growth rate (7–9%) per annum. In contrast, the annual growth of agriculture is relatively low (1.5%) compared to the service sector and GDP growth [ 40 ]. The total investment in agriculture has been reduced from 2.43 to 1.28% during 1979–80 to 2007–08 period [ 28 ]. The expenditure on subsidies, maintenance of existing projects, the relatively lower allocation for irrigation, rural infrastructure and research, lack of adequate credit support, and credit infrastructure in rural areas are the drivers of slow growth in public investment in agriculture [ 43 ]. Given this high food price inflation, researchers and policymakers have raised severe concern about reducing the food price inflation because most of the population spend half of the income on food expenditure, and food containing a larger share in the CPI basket. Therefore, it is necessary to find the causes and suitable majors to reduce food price inflation.

The present study contributes to food price inflation literature in several ways. First, a wide range of studies has investigated the drivers of food price inflation in India. The various demand and supply-side factors, namely, per capita income, growth of money supply, changing patterns of the consumer's dietary habits, high agricultural wages, speculations, and low growth of agricultural productions, are accountable for high food inflation. However, the results are ambiguous and vary considerably across countries due to different data periods and econometric methodologies applied in their studies. Second, the change in macroeconomic factors may have a substantial effect on food price inflation. For instance, if the food prices positively impact money supply, the consumer suffers from welfare loss. If it negatively effects on food prices, the producer suffers from welfare loss. However, this relationship of macroeconomic factors has not empirically analyzed significantly with respect to food price inflation in India. Third, various studies have explored the impact of macroeconomic factors on food price inflation across the world. For example, Kargbo [ 24 ] for Eastern and Southern Africa, Kargbo [ 25 ] for West Africa, Reziti [ 38 ] for Greek, Kargbo [ 26 ] for South Africa, Yu [ 46 ] for China and Sasmal [ 40 ]. Nevertheless, few studies have empirically examined the impact of selected macroeconomic factors on food price inflation by incorporating a control variable like per capita net availability of food grain into account. To the best of my knowledge, there is no study existing in the context of India. Fourth, most of the studies have taken WPI food indices, food items from only primary food articles or some of the index of selected food items, such as cereals and pulses, fruits and vegetables, milk and milk products, egg, meat, and fish as a measure of food price inflation. However, the present study has used the combined price index for industrial worker food (CPI-IW-F). Fifth, numerous studies have concluded that food price inflation is triggered by supply-side factors (see, [ 11 , 17 , 33 ]). However, to examine the rise in food price inflation, we have included both demand and supply-side factors in our study. Six, the present study also considered that food price inflation is not only influenced by domestic factors but also by global factors. More specifically, changes in global food prices and the exchange rate might positively and significantly impact food price inflation. However, the effect of these external factors on food price inflation does not explain the extent of food price inflation driven by domestic supply-side factors. For this purpose, we have included the per capita net availability of food grain as a control variable in the model. Suppose the demand for agricultural food items rises remarkably owing to a surge in macroeconomic factors. However, the supply of food items failed to meet the demand proportionately, then food items prices will go up. Therefore, the goal of the present study is to analyze the long-run and short-run impact of macroeconomic factors on food price inflation and verify the causal relationship aspect of these variables in the case of India over the period January 2006–March 2019.

The remaining of the paper is structured as follows. “ Literature review ” section follows the review of the literature on the relationship between macroeconomic factors and food price inflation. “ Methods ” section represents data and methodology. “ Results and discussion ” section discusses the results of the study. “ Conclusions ” section provides conclusive remarks and policy implications.

Literature review

This paper aims to examine the impact of macroeconomic factors on food price inflation. This section provides a review of the literature to establish the empirical basis of the link between macroeconomic factors and food price inflation.

Per capita income and food price inflation

Per capita income has a positive impact on food price inflation via increasing purchasing power of the money in the hands of the people, which leads to a surge in demand for food items resulting in a rise in food prices. Carrasco and Mukhopadhyay [ 10 ] argued that per capita income is positively affected food prices in three South Asian economies. However, the decline in agricultural production increases food prices up, and magnitudes are varying across countries. Agrawal and Kumarasamy [ 1 ] documented that food price inflation rose with the response to increases in India’s per capita income. They also suggested a 1% surge in per capita income upsurges the demand for fruits, vegetables, milk, and edible oil by 0.55–0.65%, and animal products by 0.38%. However, it reduces the demand for cereals and pulses by 0.05% and 0.20%, respectively. Joiya and Shahzad [ 22 ] and Sasmal [ 40 ] reported the same findings in Pakistan and India, respectively. In contrast, the study also found a negative association between food price inflation and per capita income. Kargbo [ 24 ] in Ethiopia and Malawi among Eastern and Southern African countries, Kargbo [ 25 ] for Cote d'Ivoire of West African countries.

Money supply and food price inflation

An increase in the money supply positively affects food price inflation through market credit facility by generating aggregate demand. However, it reduces food prices by creating investment via availing credit to the producer. Numerous studies have investigated the impact of money supply on food price inflation across the world. For example, Mellor and Dar [ 29 ] found that the expansion of money supply largely determines upward pressure on food grains prices. Barnett et al. [ 5 ] found that money supply positively affects food inflation and agricultural commodity prices in the U.S. Similar results were found by Kargbo [ 26 ] and Asfaha and Jooste [ 3 ] for South Africa. Further, Bhattacharya and Jain [ 8 ] concluded that an unexpected monetary tightening induces food price inflation in emerging and developed countries. However, a negative relationship is established between money supply and food prices for Kargbo [ 24 ], Kargbo [ 25 ], and Yu [ 46 ] for Eastern and Southern African countries and West African countries and China.

Exchange rate and food price inflation

The depreciation of the real exchange rate increases food price inflation by expanding the cost of importing petroleum products, fertilizer, and other finished products relating to agricultural commodities, leading to rising domestic market prices. In other words, depreciation of the exchange rate directly affects the agricultural sectors vi changing the prices of tradable and non-tradable goods resulting in a change in the prices of agricultural products in favor of the farmer. Taylor and Spriggs [ 45 ] showed that the exchange rate has a greater influence on volatility of agricultural prices in Canada. Similarly, Mitchell [ 30 ] and Mushtaq et al. [ 32 ] and Iddrisua and Alagidede [ 19 ] also concluded that the depreciation of the exchange rate is positively affected food prices in the U.S., Pakistan and South Africa, respectively. In contrast to this, Cho et al. [ 12 ] confirmed that change in the exchange rate has a negative impact on relative agricultural prices. However, Sasmal [ 40 ] found no significant relationship between the exchange rate and food price inflation in India during 1971–2012.

Global food price and food price inflation

The increase in the global food price of the commodity can influence the domestic price via international trade mechanism. The export increases as the global food price increases resulting in a decrease in domestic market supply followed by a hike in prices. On the contrary, the rise in import raises the domestic substitute food item’s price followed by a surge in domestic market price. Robles [ 39 ] indicated that the international prices transmission has a positive impact on the domestic agricultural market in Asian and Latin American countries. Gulati and Saini [ 16 ] revealed that the global food price index is positively impacted food price inflation in India. Similarly, Baltzer [ 4 ] states that an increase in international prices promotes domestic prices in the case of Brazil and South Africa. However, the price.

transmission is very limited in China and India. Lee and Park [ 27 ] confirmed that the lagged values of global food price inflation are positively impacted food price inflation in 72 countries. Selliah et al. [ 41 ] revealed that an increase in global food price increases domestic food prices in both the short and long run in Sri Lanka. Similarly, Holtemöller and Mallick [ 17 ], Bhattacharya and Sen Gupta [ 6 ], and Huria and Pathania [ 18 ] also documented that global food price shocks have a significant and positive inflationary trend on food inflation in India. However, Rajmal and Mishra [ 37 ] pointed out a limited transmission of prices from international food prices to domestic prices in India.

Agricultural wage and food price inflation

One of the significant public work programs is the National Rural Employment Guarantee (NREG), which promotes the real daily agricultural wage rates. On the one hand, an increase in rural wages can induce food prices by increasing production costs. On the other hand, it raises food prices via higher purchasing power, resulting in higher wages, which boosts the demand for food items. Gulati and Saini [ 16 ] revealed that domestic farm wages are positively associated with food price inflation in India. Goyal and Baikar [ 15 ] showed that the rapid increase in MGNREGA wages when it merged with inflation boosts agricultural wages rather than the implementation of MGNREGA across India. Bhattacharya and Sen Gupta [ 6 , 7 ] examined the drivers of food price inflation in India over the period 2006–2013. The structural vector error correction model (SVECM) showed that agricultural wage inflation promotes food price inflation after the implementation of MNGREGS.

The above literature review shows that both demand and supply-side factors have contributed to food price inflation. Many studies have investigated the impact of macroeconomic factors on food price inflation across the globe. However, only a few studies have been directed, which empirically examined the effect of macroeconomic factors on food price inflation by incorporating per capita net availability of food grain and agricultural wages in a multivariate framework. So far as we know, there is no study available in the case of India in this regard employing monthly data over the period January 2006–March 2019. Hence, our study attempts to fill this gap.

The present study makes use of monthly time series data on per capita GDP (Y), real exchange rate (EX), money supply (M3), global food price index (GF), per capita net availability of food grain (NFG), agricultural wages (AW) and combined price index-industrial workers for food (CPI-IW-F) indices as a proxy for food price index (FP) during January 2006–March 2019. The data on per capita GDP, real exchange rate, money supply is collected from the Reserve Bank of India (RBI), whereas combined price index-industrial workers for food and agricultural wages are retrieved from the Ministry of Labor Bureau, Government of India. The data on per capita net availability of food grain and real global food price index are obtained from the Directorate of Economics and Statistics, Department of Agriculture & Farmers Welfare, Government of India, and the Food and Agriculture Organization of the United Nations, respectively. Monthly data on per capita net availability of food grain and per capita GDP is not available in the case of India. Therefore, we have used the linear interpolation method to get the monthly data for this variable. Footnote 1 The selection of the data period has been considered based on the availability of uniform and consistent monthly data over a period of time. We use high-frequency data while working on macroeconomic variables to capture the true impact of it [ 31 ]. Further, data on food price inflation is volatile, measuring the impact of macroeconomic factors on food inflation using high-frequency data, namely, weekly and monthly, provides accurate estimates rather than annual series. Since, data on a targeted variable i.e., food inflation is not available on a weekly basis for a longer period in the case of India. Therefore, we have used monthly data for this purpose.

The real exchange rate (EX) is measured as the real effective exchange rate which is trade based weighted average value of Indian currency against 36-currency bilateral weights, per capita income (Y) is measured as the percentage change in per capita gross domestic product, money supply (MS) is measured as broad money (MS), global food prices (GF) are measured as a real global food price index, and agricultural wages (AW) is measured as average daily wage rates from agricultural occupations; per capita net availability of food grain (NFG) is measured as gross production plus net imports plus stocks. Finally, food price inflation (FP) is measured as combined price index-industrial workers for food index (CPI-IW-F). The food inflation was experienced in India from 2006 onwards. However, the CPI-combined series is used and available from 2014 onwards to measure the official inflation rate. To get a more extended frequency of data on food inflation series, we have used consumer price index-industrial workers for food (CPI-IW-F) as a proxy for food inflation measures. We select to use CPI-IW-F because Bicchal and Durai [ 9 ] and Goyal [ 14 ] established that CPI-IW and CPI-combined have similar properties with CPI-IW is available for a more extended period. All the variables are seasonally adjusted using CENSUS X13 and converted into the natural logarithm form except per capita GDP.

Unit root tests

One should necessarily check the properties of all the variables before commencing any econometric techniques as it gives spurious and invalid results. The ARDL technique requires to check the integration properties of the selected variables to confirm that none of the variables should follow I (2) process, which seems to be invalid and unsuitable for applying the ARDL approach. Therefore, we use the ADF and PP tests to check the order of integration of the variables.

ARDL bounds testing approach to cointegration

We employ the ARDL bounds testing approach to cointegration propounded by Pesaran and Shin [ 35 ] and Pesaran et al. [ 36 ] in order to examine the long-run and short-run association between macroeconomic factors and food price inflation in India. This method is superior over other traditional approaches of Johansen and Juselius [ 21 ] and Johansen [ 20 ] cointegration on the following grounds. First, it is one of the most popular and flexible methods. It does not impose any restriction on any nature of data and can be applied irrespective of all the order of integration I (1) or I (0) or both mix. Second, as noted by Pesaran and Shin [ 35 ] that ARDL estimators give the true parameters, and coefficients are super consistent as compared to other long-run estimates, especially when the sample size is small. Third, it also helps to eradicate the problem of the endogeneity that appears in the model. Fourth, it is even able to capture both short-run and long-run estimates simultaneously. The unrestricted error correction models (UECM) of the ARDL model can be represented as follows:

where ∆ denotes first difference operator; \({\varepsilon}_{t}\) is the error term; \({\alpha }_{1}\) , \({\alpha }_{2}\) , \({\alpha }_{3}\) , \({\alpha }_{4}\) , \({\alpha }_{5}\) , \({\alpha }_{6}\) , and \({\alpha }_{7}\) are the constant; \({\alpha }_{F}\) , \({\alpha }_{Y}\) , \({\alpha }_{M}\) , \({\alpha }_{E}\) , \({\alpha }_{G}\) , \({\alpha }_{NF}\) , and \({\alpha }_{A}\) are the long-run coefficients; \({\beta }_{h}\) , \({\beta }_{i}\) , \({\beta }_{j}\) , \({\beta }_{k},{\beta }_{l}, {\beta }_{m}\) and \({\beta }_{n}\) are the short-run coefficients.

The optimal lag selection has been made based on the Akaike Information Criteria (AIC). The primary step in the ARDL model is to estimate the Eqs. ( 1 – 7 ) by ordinary least squares (OLS). The long-run relationship is determined based on the F test or Wald test for the coefficient of the lagged levels of the variables. The null hypothesis of no long-run relationship, \({H}_{0}:{\alpha }_{F}={\alpha }_{Y}={\alpha }_{M}={\alpha }_{E}={\alpha }_{G}={\alpha }_{NF}={\alpha }_{A}=0\) against the alternative hypothesis of the long-run, \({H}_{1}:{\alpha }_{F}\ne {\alpha }_{Y}\ne {\alpha }_{M}\ne {\alpha }_{E}\ne {\alpha }_{G}\ne {\alpha }_{NF}\ne {\alpha }_{A}=0\) referred to the equation follows as (FP/Y, MS, EX, GF, NFG, AW). According to Pesaran et al. [ 37 ], the null hypothesis of no long-run association can be rejected if F -statistics is greater than the upper critical bound (UCB). It suggests that there is a long-run association among the variables. While, test statistics falls below the lower critical bound (LCB), null hypothesis cannot be rejected. It suggests that there is no long-run association among the variables. If the calculated value falls between the lower and upper critical points, the result is inconclusive. Because the two asymptotic critical values bound lower value (assuming the regressors are I (0)) and upper (assuming purely I (1) regressors) provide a test for cointegration.

After identifying the long-run relationship among the variables, our next step is to apply the vector error correction model to examine the directions of causality among the variables in both the short-run and long-run. The model of VECM can be written as follows.

where \(\Delta\) is the difference operator; \({ECM}_{t-1}\) is the lagged error correction term, which is derived from the long-run cointegration relationship; \({\varepsilon}_{1t}\) , \({\varepsilon}_{2t}\) , \({\varepsilon}_{3t}, {{\varepsilon}_{4t}, \varepsilon}_{5t}, {\varepsilon}_{6t}\) and \({\varepsilon}_{7t}\) are the random errors; \({\gamma }_{1}\) , \({\gamma }_{2}\) , \({\gamma }_{3, }{\gamma }_{4, }{\gamma }_{5, }{ \gamma }_{6}\) and \({\gamma }_{7}\) are the speed of adjustments. The long-run relationship among the variables indicates that there is a presence of Granger-causality at least one direction, which is determined by F -statistics and lagged error correction term. The short-run causal relationship is represented by F- statistics on the explanatory variables while long-run causal relationship is represented by t-statistics on the coefficient of the lagged error correction term. The error correction term ( \({ECT}_{t-1}\) ) is negative and statistically significant (t-statistic) at the 1% significance level.

Results and discussion

Preliminary analysis.

A preliminary analysis is conducted using commonly used descriptive statistics. We also reported the summary of descriptive statistics of all the considered variables during the study period in Table 1 . The results revealed that the average food price index and the real exchange rate is 5.375% and 4.687% during the study period. However, the average money supply and real global food price index is 11.185% and 4.619%. The per capita net availability of food grain and agricultural wages is 5.130% and 6.931% whereas, per capita income is 0.445%, which is lower than other variables across the sample period. The results of the correlation matrix are represented in Table 2 . The correlation analysis results revealed that per capita income, money supply, real exchange rate, real global food price index, per capita net availability of food grain and agricultural wages are positively associated with food price inflation. For instance, food price inflation is highly correlated with per capita income, money supply, real exchange rate, per capita net availability of food grain, and agricultural wages. It suggests that macroeconomic factors might be promoting food price inflation in India. Similarly, per capita income is positively correlated with money supply, exchange rate, and per capita net availability of food grain, and agricultural wages. Further, there is a high positive correlation between agricultural wages and per capita net availability of food grain.

Results of unit root tests

To avoid spurious and invalid results of all the non-stationary data, we have checked the integration properties of all the variables and confirm that none of the variables follows the I (2) process. Therefore, the ADF and PP unit root tests are used to check the order of integrations of the variables. The results of unit root tests are reported in Table 3 . It indicates that food price inflation (FP), per capita income (Y), money supply (MS), real exchange rate (EX), real global food price index (GF), per capita net availability of food grain (FG) and agricultural wages (AW) are integrated of order I (1).

Results of ARDL cointegration tests

The above unit root test results show that all variables follow a same order of integration, i.e., I (1). Therefore, we apply the ARDL technique to check the long-run relationship among the variables using Eqs. ( 1 )-( 7 ) during January 2006–March 2019. Here, the optimal lag length is 2, according to VAR lag order selection criteria. The results of the ARDL model are presented in Table 4 . The result shows that calculated F -statistics (4.155) is larger than UCB at the 5% level of significance when food price inflation is considered a dependent variable (FP/Y, MS, EX, GF, NFG, WA). It indicates that there is a long-run relationship among food price inflation (FP) and per capita income (Y), money supply (MS), real exchange rate (EX)), global food prices (GF), per capita net availability of food grain (NFG), and agricultural wages (WA). Likewise, calculated F- statistics (11.043) is also larger than UCB at the 5% level of significance when per capita income is considered a dependent variable and integrated order (1). Therefore, UCB is applied to establish a long-run relationship among the variables. Likewise, calculated F- statistics (10.239) is also larger than UCB at the 5% level of significance when money supply (MS) is considered a dependent variable. Similarly, calculated F- statistics (3.335) is also larger than UCB at the 10% level of significance when global food price (GF) is considered a dependent variable. However, calculated F -statistics is lower than UCB when the exchange rate (EX), per capita net availability of food grain (NFG), and agricultural wages (AW) serve as dependent variables. It suggests a there is no long-run relationship among the variables when the exchange rate, per capita net availability of food grain and agricultural wages are the dependent variables.

Results of long-run and short-run estimates

The cointegration test results based on the ARDL model revealed the long-run equilibrium relationship among the variables. However, these results do not explain the cause-and-effect association among the food price inflation and macroeconomic factors, namely, per capita income, money supply, exchange rate, global food prices, per capita net availability of food grains, and agricultural wages. Hence, we have investigated the impact of macroeconomic factors on food price inflation in this part. It is better to check the long-run effect of macroeconomic factors on food price inflation after confirming the cointegration relationship among the variables when food price inflation is considered the dependent variable. The results of the long-run analysis are reported in Table 5 in panel-I. The long-run results illustrate that per capita income is positively and significantly impacted food price inflation. It implies that a one unit increase in per capita income induces food price inflation by 0.14 unit. The rise in per capita income raises the purchasing power of the money, which leads to a surge in demand for food items resulting in a hike in food prices. The results of our study similar to Carrasco and Mukhopadhyay [ 10 ] in three South Asian economies, Agrawal and Kumarasamy [ 1 ] in India, Joiya and Shahzad [ 22 ] in Pakistan and Sasmal [ 40 ] in India. However, our result is inconsistent with Kargbo [ 24 ] and Kargbo [ 25 ], who revealed a negative relation between the variables in Ethiopia and Malawi, and in Cote d'Ivoire, respectively.

Similarly, a 1% increase in money supply increases food price inflation by 0.36%. It implies that the rise in money supply puts upward pressure on food price inflation and is significant at the 1% level of significance. Money supply is positively affecting food price inflation by generating aggregate demand in the market, which pushes the food prices up. This finding is consistent with Kargbo [ 24 ] for Kenya, Sudan, and Tanzania among the Eastern and Southern African countries and contradictory with Sasmal [ 40 ] who did not find any long-run relationship between money supply and food price inflation in India and Yu [ 46 ] for China who confirmed that monetary policy expansion has a negative impact on prices of seven major food products in the long-run. Similarly, a rise in the real exchange rate has a downward pressure on food price inflation. It indicates that a 1% increase in the real exchange rate will have a negative impact on food price inflation by 0.30%. The increase in the real exchange rate reduces food prices by lowering the import of petroleum products, fertilizer, and other products relating to agricultural commodities in the long run. Hence, organic fertilizers can be used to produce commercial food products to reduce the dependency on fertilizers, which may maintain price stability and reduce the negative welfare impact on food prices. This outcome is consistent with Cho et al. [ 12 ] and is inconsistent with Iddrisua and Alagidede [ 19 ] in South Africa, Durevall et al. [ 13 ] in Ethiopia. Further, per capita net availability of food grain has a negative impact on food price inflation. In other words, there is an inverse relationship between per capita net availability of food grains and food price inflation in India. It suggests that a 1% increase in per capita net availability of food grains reduces food price inflation by 0.69%. The increase in the supply of net food availability in the domestic market by increasing food production can reduce food price inflation. On the other hand, if the supply of food grain availability declines due to crop failure, it increases food price inflation. Therefore, the government should increase domestic food production and reduce the exports of commodities at the time of food inflation to maintain stability in prices. Further, agricultural production is seasonal, and it is highly correlated to the month of food harvest. The stock of food grain during harvest season can avoid the off seasonal food price inflation. Increasing the stock of food items by establishing a larger cold storage system and strengthen and widening the existing warehouses can also help to control food inflation in India. This result is similar to Kargbo [ 25 ] in Cote d’Ivoire and Nigeria and Carrasco and Mukhopadhyay [ 10 ] in three South Asian economies and inconsistent with Sasmal [ 40 ], who failed to establish a significant relationship between agricultural food production and food price inflation in India in the long-run. Furthermore, our results revealed that food price inflation rose with the response to increases in global food prices. It suggests that a 1% surge in global food price upsurges food price inflation by 0.13%. This result is consistent with Selliah et al. [ 41 ] for Sri Lanka, Holtemöller and Mallick [ 17 ] for India, and Huria and Pathania [ 18 ] for India. However, Rajmal and Mishra [ 37 ] and Baltzer [ 4 ] pointed out a limited transmission of prices from international food prices to domestic prices in India. The extent of transmission of global food prices on price hike in the domestic market depends on at which magnitudes commodity’s international trade takes place. Finally, our study results also found that agricultural wages have a positive and significant impact on food price inflation at the 1% level of significance. It implies that a 1% surge in agricultural wages increases the food price inflation by 0.31% in the long-run. The rise in wage rate via welfare-oriented-schemes like MNGREGS increases the bargaining and purchasing power of money, increasing in demand for food items followed by increased food inflation. The increase in the agricultural wage rate should be substituted with food price inflation by increasing productivity. Hence, the increase in demand for food originated by a hike in the agricultural wage rate can be substituted by raising the productivity of each worker. A similar result is found by Bhattacharya and Sen Gupta [ 7 ] for India.

After having discussed long-run results, we shall move in to discuss with reference to the short-run. The results of the short-run analysis are reported in Table 5 in panel-II. The short-run analysis indicates an increase in per capita income and money supply is positively related to food price inflation in the short-run as the coefficients of these variables are statistically significant. Similarly, food price inflation rises with the increase in global food prices. Further, the real exchange rate has a positive impact on food price inflation in the short-run. However, the result is not significant. Moreover, agricultural wages have a positive impact on food price inflation. It implies that an increase in agricultural wages raises food price inflation in the short run. The outcome is consistent with Huria and Pathania [ 18 ] for India. However, per capita net availability of food grain is negatively and significantly impacted food price inflation. It suggests that a 1% increase in food grain availability decreases food price inflation by 0.11% in the short-run. In contrast, a decrease in the growth rate of food grain availability increases food price inflation. This finding is similar to Kargbo [ 25 ] in Cote d’Ivoire and Senegal among West African countries. Finally, the results also documented lagged food price inflation positively impacts present food price inflation. It suggests that a 1% increase in lagged food price upsurges food price inflation by 0.36% in the short run.

The sign of lagged ECT is negative and significant at the 1% level, which implies that short-run deviation from food prices can be restored toward the long-run equilibrium with a 16.8% speed. The model has satisfied all the diagnostic tests. This model is free from autoregressive conditional heteroscedasticity; the functional form of the model is well specified, which is represented by the Ramsey RESET coefficient.

Results of VECM Granger causality test

After identifying the long-run association between macroeconomic factors and food price inflation, we have employed the VECM Granger causality test to examine the directions of causality among the variables in both the short-run and long-run. The Granger causality results are represented in Table 6 . The outcomes of the short-run causality tests are obtained from the F -statistics of lagged independent variables, while the results of long-run causality are obtained from the negative and significant coefficients of t-statistics of lagged error correction term. The results are reported in Table 6 and show that a short-run bidirectional causality is confirmed between per capita income, exchange rate, and food price inflation at a 1% level. This finding is opposite of Sasmal [ 40 ], who reported a unidirectional causality running from per capita income to food price inflation in India. Similarly, a bidirectional causality is existed between percapita net availability of food grain and food price inflation in the short run. It implies that the increase in food grain availability reduces food price inflation by increasing domestic food grain production on the one hand. Whereas on the other hand, an increase in food price inflation also leads to a rise in food grain availability by rising demand for food products. Further, there is a unidirectional causality running from global food prices to food price inflation. It suggests that an increase in global price attracts exporters to increase their supply of food items to the global market to get high profit, which eventually decreases the domestic market supply, resulting an in a price increase. However, there is no causal relationship running from money supply and agricultural wages to food price inflation in the short run.

There is an existence of a bidirectional causal relationship between global food prices and per capita income. However, no causality runs from money supply, exchange rate, per capita net availability of food grain, and agricultural wages to per capita income. A short run unidirectional causality is established from food price inflation, exchange rate, global food prices, and per capita net availability of food grain to money supply. A bidirectional causality has existed between agricultural wages and money supply in the short run. Further, unidirectional causality is running from per capita income, the exchange rate to global food prices. A unidirectional causal relationship is found from per capita income, money supply, the exchange rate, and global food prices to per capita net availability of food grain in the short run. Moreover, short-run unidirectional causality is confirmed from food price inflation, per capita income, the exchange rate and global food prices to agricultural wages.

Moving to the long-run causality, the coefficients of \({ECM}_{t-1}\) are negative and statistically significant in Eq. ( 8 ), where money supply, global food prices, and per capita net availability of food grain are the dependent variables. Therefore, results revealed a bidirectional causality among the money supply, global food prices, and per capita net availability of food grain production in the long-run.

Conclusions

This study aimed to examine the impact of macroeconomic factors on food price inflation in India during January 2006–March 2019. To consider the short-run dynamics and the long-run analysis and directions of causality among the variables, we have applied the ARDL model and Granger causality test in our study. The ARDL results have shown evidence of the long-run association among the macroeconomic factors and food price inflation. The long-run result show that percapita income, money supply, global food price, and agricultural wages have a positive and significant impact on food price inflation of India in both the long-run and short run. However, the per capita net availability of food grain negatively impacts food price inflation. It implies that an increase in food grain availability reduces food price inflation in both the short and long run. Further, the real exchange rate is positively affecting food price inflation. However, it is insignificant in the short-run. The Granger causality estimates show that a short-run bidirectional causality is confirmed among per capita income, the exchange rate, per capita net availability of food grain, and food price inflation. Further, there is evidence of unidirectional causality running from global food prices to food price inflation. However, there is no causal relationship running from money supply and agricultural wages to food price inflation in the short run. The long-run results revealed a bidirectional causality among the money supply, global food prices and per capita net availability of food grain.

Given these results, the paper makes important contribution to the macroeconomic factors and food price inflation in India. The significant policy suggestions are that the growth in money supply promotes food price inflation in the long-run, which affects the welfare of the poor consumer as the majority of the people depend on agriculture. It also positively affects market credit facility by generating aggregate demand followed by changes in relative prices across commodities, which push the food prices up. Therefore, the government should adopt effective policy measures to protect consumers from higher food prices. These are the effectively implementation of public distribution systems, policies for food security, and reducing the money supply via adopting a contractionary monetary policy, which eventually reduces food price inflation by reducing demand for food items. Further, the increase in global food inflation triggers food price inflation by international trade channels. However, the influence of global food inflation on food price inflation can be moderated by introducing a flexible tariff structure. Hence, the government should introduce stable and liberal trade policies that reduce food price inflation without compromising farmers remuneration values.

Moreover, our result also revealed that an increase in the net availability of food grain reduces food price inflation in both the short and long run. Therefore, the government should take necessary steps in favor of an increase in domestic food production. The high yielding variety (HYV) seeds, easily accessible credit facilities should be available to the farmer, increasing the domestic agricultural food production, thereby reducing the import of agricultural goods through the exchange rate and their adverse impact on food inflation. The stock of food grain during harvest season can avoid off seasonal food inflation. The increasing the stock of food items by establishing an extensive cold storage system and strengthening large warehouses can control food inflation in India. Furthermore, the rise in agricultural wages boosts food price inflation. The increase in the agricultural wage rate should be substituted with food price inflation by increasing labor productivity. Hence, the increase in demand originated by a hike in the agricultural wage rate can be substituted by raising each workers productivity.

Our results also found that per capita income Granger causes food price inflation both in the short-run. In this respect, we can say that there is a huge sectoral imbalance among the sectors. The government should be more focused on the agricultural sector and its growth and productivity by allocating massive funds in the irrigation, agricultural research, and innovation of modern technology and its adaptation in agriculture instead of spending on the name of social security and welfare of the poor. Therefore, balanced and sustainable growth and stability can be achieved for a developing country like India. The real exchange rate and food price inflation Granger causes to each other. The depreciation of the real exchange rate increases the food price inflation via expanding the import of petroleum products, fertilizer, and other finished products relating to agricultural commodities, which are very expensive. The increasing import of these products promotes food price inflation by raising domestic prices. Hence, to reduce the food price inflation, the government should increase the domestic agricultural production to meet our demand for food items rather than importing from other countries.

Availability of data and materials

Data used in the study are available in the Reserve Bank of India, Ministry of Labor Bureau, Directorate of Economics and Statistics, Department of Agriculture & Farmers Welfare, Government of India, and the Food and Agriculture Organization of the United Nations.

By using the linear interpolation method, we have converted the annual data into the monthly time series data. Because the high-frequency data increases the power of a statistical test and provide robust results [ 48 ]. The interpolation method has been widely used in the empirical analysis [ 34 , 42 , 44 ].

Abbreviations

Autoregressive distributed lag

Combined price index

Wholesale price index

Reserve Bank of India

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Asharani Samal & Phanindra Goyari

School of Business, Woxsen University, Hyderabad, 502345, India

Mallesh Ummalla

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Samal, A., Ummalla, M. & Goyari, P. The impact of macroeconomic factors on food price inflation: an evidence from India. Futur Bus J 8 , 15 (2022). https://doi.org/10.1186/s43093-022-00127-7

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DOI : https://doi.org/10.1186/s43093-022-00127-7

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Home » Managerial Economics » Case Study: Inflation in India

Case Study: Inflation in India

Knowing Inflation

By inflation one generally means rise in prices. To be more correct inflation is persistent rise in the general price level rather than a once-for-all rise in it, while deflation is persistent falling price. A situation is described as inflationary when either the prices or the supply of money are rising, but in practice both will rise together. These days economies of all countries whether underdeveloped, developing as well developed suffers from inflation. Inflation or persistent rising prices are major problem today in world. Because of many reasons, first, the rate of inflation these years are much high than experienced earlier periods. Second, Inflation in these years coexists with high rate of unemployment, which is a new phenomenon and made it difficult to control inflation.

An inflationary situation is where there is ‘too much money chasing too few goods’. As products/services are scarce in relation to the money available in the hands of buyers, prices of the products/services rise to adjust for the larger quantum of money chasing them.

Read More: Definition of inflation and it’s types

Inflation is no stranger to the Indian economy. The Indian economy has been registering stupendous growth after the liberalization of Indian economy. In fact, till the early nineties Indians were used to ignore inflation. But, since the mid-nineties controlling inflation has become a priority. The natural fallout of this has been that we, as a nation, have become virtually intolerant to inflation. The opening up of the Indian economy in the early 1990s had increased India’s industrial output and consequently has raised the India Inflation Rate. While inflation was primarily caused by domestic factors (supply usually was unable to meet demand, resulting in the classical definition of inflation of too much money chasing too few goods), today the situation has changed significantly.

Inflation today is caused more by global rather than by domestic factors. Naturally, as the Indian economy undergoes structural changes, the causes of domestic inflation too have undergone tectonic changes. The main cause of rise in the rate of inflation rate in India is the pricing disparity of agricultural products between the producer and consumers in the Indian market. Moreover, the sky-rocketing of prices of food products, manufacturing products, and essential commodities have also catapulted the inflation rate in India. Furthermore, the unstable international crude oil prices have worsened the situation.

Defining causes of Inflation

What exactly is the nature of this inflation which has the nation in its grip? The different causes of inflation which are experienced in Indian economy in a large proportion would be:-

• Demand-pull inflation: This is basically when the aggregate demand in an economy exceeds the aggregate supply. It is also defined as `too much money chasing too few goods’. Bare-boned, it means that a country is capable of producing only 100 items but the demand is for 105 items. It’s a very simple demand-supply issue. The more demand there is, the costlier it becomes. Much the same as the way real estate in the country is rising.
• Cost-push inflation: This is caused when there is a supply shock. This represents the condition where, even though there is no increase in Aggregate Demand, prices may still rise. I.e. non availability of a commodity would lead to increase in prices. This may happen if the costs of especially wage cost rise.
• Imported Inflation: This is inflation due to increases in the prices of imports. Increases in the prices of imported final products directly affect any expenditure-based measure of inflation. They play an important role in driving the rise in domestic prices. The rise in the global prices of crude oil and agricultural commodities, including food grains, and industrial products, and setbacks to global economy resulting from sub-prime mortgage disaster and US recession have contributed to India’s inflation.

Other Causes:

• When the government of a country print money in excess, prices increase to keep up with the increase in currency, leading to inflation.
• Increase in production and labor costs, have a direct impact on the price of the final product, resulting in inflation.
• When countries borrow money, they have to cope with the interest burden. This interest burden results in inflation.
• High taxes on consumer products, can also lead to inflation. An increase in indirect taxes can also lead to increased production costs.
• Inflation can artificially be created through a circular increase in wage earners demands and then the subsequent increase in producer costs which will drive up the prices of their goods and services.   This will then translate back into higher prices for the wage earners or consumers.   As demands go higher from each side, inflation will continue to rise.
• Debt, war and other issues that cause a drastic financial blunder can also cause the inflation.

Measuring Inflation

Inflation in India is mainly estimated on the basis of fluctuations in the wholesale price index (WPI). The wholesale price index comprises of the following indices:

• Domestic Wholesale Price Index (DWPI)
• Export Price Index (EPI)
• Import Price Index (IPI)
• Overall Wholesale Price Index (OWPI)

The WPI consists of about 435 items and has three broad categories. They are:-

• Primary Articles (weight of 22.0253) — 22% Index
• Fuel, Power, Light, and Lubricants (weight of 14.2262) –   14% Index
• Manufactured Products (weight of 63.7485) — 64% Index

The base year of the WPI is 1993-94. The base year usually chosen is one where there has been fairly less volatility. The Indian WPI figure is released weekly on every Thursday. But recently the government has approved the proposal to release a wholesale price based inflation data on a monthly basis, instead of every week. The new series of WPI based inflation with 2004-05 as the base year would be launched soon. The move is aimed at improving the accuracy of the inflation data.

The monthly release of WPI is a widely-followed international practice. And, it is expected to improve the quality of data. Collection of price data of manufactured products will, accordingly, have a monthly frequency consistent with the practice of release of WPI. The new series of WPI based inflation with 2004-05 as the base year would be launched soon. However, the government will continue to release a weekly index for primary articles, and commodities in the fuel, power, light and lubricants groups. The weekly index will facilitate monitoring of prices of agricultural commodities and petroleum products, which are sensitive in nature.

Problems of Inflation

It has been reported that the manufacturing capacity in India is running around 95 per cent, which usually means it is running at full capacity. Therefore, when the price of manufactured products is increasing, it means that demand is usually higher than supply and that is a clear case of demand-pull inflation.

On the primary goods front, which consists of fruits, vegetables, food-grains etc, it is not that straight-forward. It has certainly been all over the news that the prices of fruits and vegetables are increasing and a trip to the supermarket or local grocery shop will testify to that. Although it is a clear case of demand-pull inflation, on the other, it is also a bit of a supply shock when one considers the fact that there is an abnormally high percentage of fruits and vegetables that goes to waste because of the lack of cold-storage facilities. Some estimates say 50 per cent of produce goes to waste and that is a conservative number.

The fuel price hike is a straight example of cost push inflation. When OPEC (The Organization of the Petroleum Exporting Countries) was formed, it squeezed the supply of oil and this caused oil prices to rise, contributing to higher inflation. Since oil is used in every industry, a sharp rise in the price of oil leads to an increase in the prices of all commodities.

The in depth problems due to inflation would be:

• When the balance between supply and demand goes out of control, consumers could change their buying habits, forcing manufacturers to cut down production.
• Inflation can create major problems in the economy. Price increase can worsen the poverty affecting low income household.
• Inflation creates economic uncertainty and is a dampener to the investment climate slowing growth and finally it reduce savings and thereby consumption.
• The producers would not be able to control the cost of raw material and labor and hence the price of the final product. This could result in less profit or in some extreme case no profit, forcing them out of business.
• Manufacturers would not have an incentive to invest in new equipment and new technology.
• Uncertainty would force people to withdraw money from the bank and convert it into product with long lasting value like gold, artifacts.

The imbalances inflation has created in the Indian economy:-

• It has created a new rich class in social and political lives who are corrupt themselves and also corrupt the overall society.
• The increased prices reduced the capacity to save and people preferred present consumption to future consumption.
• It has provided protection and subsides to industries which bred inefficiency.
• It has lead to misallocation of resources due to distortion of relative prices and finally a redistribution of wealth from the poor to the rich.
• It disturbs balance of payments.

Curbing Inflation

There are several reasons why we should worry about the spike in the inflation rate. Inflation is a tax on the poor and long-term lenders. Inflation is already too high, though it is definitely not at economy-wrecking levels. But it’s best to be serious about the threat it poses. Inflation has emerged as the biggest risk to the global outlook, having risen to very high levels across the world, levels that have not been generally seen for a couple of decades.

Currently, in India, we go through boom-and-bust cycles; sometimes GDP growth rates are very high and sometimes GDP growth rates drop sharply. This boom-and-bust cycle is unpleasant for every household. There is a powerful international consensus that stabilizing inflation reduces this boom-and-bust cycle of GDP growth.

India is facing the problem of inflationary pressure because of the increase in Aggregate Demand while Aggregate Supply is respectively constant. The inflationary pressure faced by Indian Economy is due to Demand-Pull inflation i.e. Aggregate Demand > Aggregate Supply. Thus to curb inflation need to fill the gap between Aggregate Demand and Aggregate Supply. For this either we need to increase Aggregate Supply or decrease Aggregate Demand that can hamper economic development. To increase Aggregate Supply either there is a need to increase production capacity of all current production units or to build new production plants.

But as quoted in a survey done by RBI that all the production plants are running at their full production capacity thus all resources are full employed. The other way is to build new plant but to do this will take at least 18months to 2years. Thus meanwhile we need to decrease Money Supply, which is opted by RBI. Increasing production of useful goods and services is what India should focus on.

As in the short run it is not possible to meet the gap between Aggregate Demand and Aggregate Supply thus RBI is planning to decrease liquidity by reducing Money Supply from the market. RBI planned that Liquidity from the market can be drained by decreasing money supply and to do so it is increasing CRR, repo rate, reverse repo rate and taking other measure like that.

CRR i.e. Cash Reserve Ratio (Liquidity Ratio) is the percentage of deposit that a commercial bank needs to keep with RBI by which RBI control liquidity in the market and create Money Supply. Repo Rate is the rate at which RBI lends money to other commercial Banks.

The Reserve Bank said that such decisions had been taken to curb inflation in India. RBI is taking positive steps to reduce the inflation since inflations rates are going up week by week. By raising the reserve rate, a deflationary pressure can be put on the economy, since the money multiplier has been reduced. People will therefore save more. But in this hike, there is negative impact in terms of higher interest rates and personal loans, vehicle loans and other loans become costly. RBI may hike the rate to reduce the money circulation in the country but it also decreased the sales of all loan items and further it reduces the manufacturing activity of many industries. Now the public and private sector banks may raise the interest rate at which they lend money to borrowers.

Produce more exports than imports than another country, then your money deflates with respect to that currency. Exporting becomes a problem cause buyers from outside feel that the goods are expensive so they prefer buying some other country’s goods with cheaper rate. Thus money does not come in. in the same way, when public has more money they buy foreign goods, thus money goes out which is bad. There is a need to encourage people to purchase goods produced within the country.

It is important for policymakers to make credible announcements and degrade interest rates. Private agents must believe that these announcements will reflect actual future policy. If an announcement about low-level inflation targets is made but not believed by private agents, wage-setting will anticipate high-level inflation and so wages will be higher and inflation will rise. A high wage will increase a consumer’s demand (demand pull inflation) and a firm’s costs (cost push inflation), so inflation rises. Hence, if a policymaker’s announcements regarding monetary policy are not credible, policy will not have the desired effect.

Keynesians emphasize reducing demand in general, often through fiscal policy, using increased taxation or reduced government spending to reduce demand as well as by using monetary policy. Supply-side economists advocate fighting inflation by fixing the exchange rate between the currency and some reference currency such as gold. This would be a return to the gold standard. All of these policies are achieved in practice through a process of open market operations.

As individuals what can we do to stop Inflation?

Firstly save!!! As much of your money as possible should be saved. This will reduce the demand on the economy and hopefully reduce inflation. Do not overuse daily essentials like cooking gas, electricity etc. Cut down on inessentials when buying groceries. Look for cheaper alternatives to products that you normally buy.

Keep roads, highways, sidewalks, etc., beautified to help attract tourism and bring additional monetary into a growing economy. Stop illegal immigration. Illegal activities reap the benefits of the country but don’t pay taxes. Government-backed investment schemes such as Post Office Savings Schemes, Public Provident Funds (PPF) and National Savings Certificates (NSC) are best to invest in when inflation is slowly inching up and you are only looking at safety, not returns. Invest in short term deposits and funds, commodities and property. This will help you to slowly reach your financial goals while safeguarding your hard-earned money.

Read More: Treasury bills and inflation control

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Case study on Inflation

Introduction:

Inflation occurs when the general level of prices is rising. Inflation is being measured by using the CIP (consumer price index) weighted averages of the prices of the products. The consumer price index measures the cost of a market basket of consumer goods and services relative to the cost of that bundle during a particular base year. The rate of inflation is the percentage change in the price level: -Rate of inflation ( year-t )= (price level in year t – price level in year t-1 )/Price level in year t-1 * 100. Where t is current year and t-1 is previous year price level.

By inflation in ordinary language, we mean a process of rising price. A situation is described as inflationary when either the prices or the supply of money are rising, because in practice both will rise together. In the Keynesian sense, true inflation begins when the elasticity of supply of output in response to increase in money supply has fallen to zero or when output is unresponsive to changes in money supply. When there exists a state of full employment the conditions will be clearly inflationary, if there is increase in the supply of money. But since we do not subscribe to the classical view that there is full employment, we can say that when money supply increases it results partly in the increase of output (GNP) and it partly feeds the rise in prices. And when the supply of output lags far behind, the rise in prices is described as inflationary. In Coulborn’s words, it is a case of “too much money chasing too few goods”. Thus, inflation is generally associated with an abnormal increase in the quantity of money resulting in abnormal rise in price.

History of inflation:

Inflation is as old as market economies. Over the long haul, prices have generally risen, as the blue line reveals. Real wages meandered along until the industrial revolution. The real wage have climbed steadily since around 1800, rising than tenfold. Until 1945, the pattern was regular; price would soar during wartime and then fall back during the postwar slump. But the pattern changed dramatically after World War II. Prices and wages how travel on a one-way street upward. They rise rapidly in periods of economic expansion in recessions they do not fall but merely rise less rapidly.

Type of inflation:

Low inflation

Low inflation is characterized by that rise slowly and predictably, we might define this as single-digit annual inflation rates. When prices are relatively stable, people trust money. They are willing to hold on to money because it will be almost as valuable in a month or a year as it is today. People are willing to rite long-term contracts in money terms because they are confident that the relative prices of goods they buy and sell will not get too far out of line. Most industrial countries have experienced low inflation over the last year.

Galloping inflation

Inflation in the double or triple digit range of 20, 100, or 200 percent a year is called galloping inflation. From time to time advanced industrial countries like Italy or Japan suffer from these syndromes. Many Latin American countries, such as Argentina and Brazil, had inflation rates of 50 to 7001 percent per year the 1970s and 1980s. Once galloping inflation become entrenched, serious economic distortions arise. Generally, most contracts get indexed to a price index or to a foreign currency, like the dollar. In these conditions, money loses its value quickly, so people hold only the bare minimum amount of needed for the daily transactions. Financial markets wither away, as capital flees abroad. People hoard goods, buy houses, and never, never lend money at low nominal interest rate. A surprising finding is that economies with galloping inflation often manage to grow rapidly even though the price system is behaving so badly.

Hyper inflation

While economies seem to survive under galloping inflation, a third and deadly strains takes hold when the cancer of hyperinflation strikes. Nothing good can be said about a market economy in which prices are rising a million or even trillion percent per year. The most thoroughly documented case of hyperinflation took place in the W.R. Germany in the 1920s. Studies have found some common features of hyperinflation:-

The real demand for money falls drastically.

Relative prices become highly unstable

There is huge variation in relative price and real wage.

Causes of inflation:

The causes of inflation can be grouped into two groups: –

One is increase in demand, which is due to

Increase in money supply

Increase in disposable incomes

Increase in community’s aggregate spending on consumptions and investment goods

Excessive speculative and tendency to hoarding and profiteering on the part of producers and traders

Increase in foreign demand and hence exports

Increase in salaries wages or dearness allowance and

Increase in population

Another one is no corresponding increase in the output of goods and service, which may be due to

Deficiency of capital equipment

Scarcity of other complementary factors of production that is skilled labor, essential raw material or lack of dynamic entrepreneurs

Increase in exports for earning the required foreign exchange

Decrease in imports owing to war or restriction or imports necessitated by an adverse balance of payment and efforts to rectify it

Speculative hoarding by the produce, traders and middlemen in anticipation of a further rise in price

Drought famine or any other natural calamity adversely a affecting agricultural production and prolonged industrial unrest resulting in reduction of industrial production.

Impact of inflation on Income and Wealth

The major distribution impact of inflation arises from difference in the kinds of assets and liabilities that people hold. When people owe money, a sharp rise in prices is a windfall gain for them. Suppose you borrow 100000 TK. To buy a house and your annual interest rate is fixed and it is 10000 TK pre years. Suddenly, a great inflation doubles all income or earnings. Your nominal mortgage payment is still 10000 TK per year, but its real cost halved. You will need to work only half as long as before to make your mortgage payment. The great inflation has increased your wealth by cutting in half the real value of your mortgage debt. If you are lender and gave assets in fixed interest rate mortgage or long-term bonds, the shoe in is on the other foot. An unexpected rise in price will leave you the poorer because the dollars repaid to you are worth much less than the dollars you lent. If inflation persists for a long time, people come to anticipate it and markets begin to adapt. An allowance for inflation will gradually be built into the market interest rate.

How costly is it to stop inflation :

We asked at the outset of this section how the United States reached such high inflation rates in the early eighties and why policymakers didn’t stop inflation sooner. The answer is easy for the first part; there was not enough political will or enough of a consensus to undertake a decisive attack on inflation. This was so, in good part, because people still remember the Great Depression, with its mass unemployment and terrible nationwide despair and social unrest. The legacy of the s favors high employment. But once the government is committed to high employment levels, she is little hope for stopping inflation once and for all. We have discussed the role of politics, credibility, long-term wage contract, and expectations as standing in the way of inflation stabilization. The basic lesson from the U.S. economy through the seventies suggested that the unemployment costs of bringing down inflation, without any help from favorable supply shocks, would be enormous. The question of how large a recession would be needed to stop inflation was certainly and important one to ask in the early 1980s, when inflation was in the double digit range and presented itself as the foremost policy challenge. Some estimates of the cost of fighting inflation were overwhelming, suggesting that to get inflation from 10 percent down to zero would take more than 10 year and that unemployment would have to increase to 10 percent and stay high for many years in order to achieve this. These estimates would not, of course, encourage a policy of inflation fighting. And yet, over the 1981-1986 periods the United States achieved an impressive disinflation. How can we account for the willingness of policymakers to take the risk and how do we explain their success.

Source of inflation :

Demand-pull inflation

This represents a situation where the basic factor at work is the increase in demand for resources either from the government or the entrepreneurs or the households. The result is that the pressure of demand is such that it cannot be met by the currently available supply of output. If, for example, in a situation of full employment, the government expenditure or private investment goes up this is bound to generate an inflationary pressure in the economy.

Cost-push inflation

We can visualize a situation where even though there is no increase in aggregate demand, prices may still rise this may happen if the costs, particularly the wage costs, go on rising. Now as the level of employment increase, the demand for workers rises progressively so that the bargaining position of the workers is enhanced. To exploit this situation, they may ask for an increase in wage rates, which are not justifiable either on grounds of a prior rise in productivity or of cost of living. The employers in a situation of high demand and employment are more agreeable to concede to these wage claims because they hope to pass on these rises in costs to the consumers in the shape of higher prices. If this happens we have another inflationary factor at work.

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Netflix PESTEL/PESTLE Analysis & Recommendations

Netflix’s opportunities and the threats to its business are assessed in this PESTLE/PESTEL analysis. The company formulates its strategies based on political, economic, social/sociocultural, technological, ecological/environmental, and legal factors (PESTEL factors) in the industry and relevant entertainment markets. These PESTLE factors create opportunities and threats that impact Netflix’s competitive position and business performance. The company’s streaming service, movies, series, and games are successful, allowing for business growth. However, this PESTLE analysis indicates the dynamic nature of external factors, which requires Netflix to fine-tune its strategies accordingly. Including the factors in this PESTEL analysis into strategic decisions can optimize long-term business outcomes.

This PESTEL/PESTLE analysis of Netflix presents industry and market trends that influence the opportunities and threats relevant to the company’s business performance. Strategic effectiveness regarding these trends can improve the company’s competitive advantages in content production and streaming services. Netflix competes with media and entertainment businesses, including Walt Disney , Sony , and NBCUniversal, as well as the production and streaming operations of Apple TV Plus, Amazon Prime Video, YouTube ( Google (Alphabet) ), Facebook (Meta) , and Microsoft Movies & TV (Films & TV). Success in this competitive environment, detailed in the Five Forces analysis of Netflix , depends on strategies for the external factors in this PESTLE/PESTEL analysis.

Political Factors

This component of the PESTLE analysis considers governmental policies and their impact on companies in the media and entertainment industry. The following are the political factors relevant to Netflix:

• Geopolitical tensions and trade bans and sanctions (threat)
• Political censorship (threat)
• Governmental support for sociocultural or national promotion through film (opportunity)

Netflix’s business growth in the entertainment industry and online service market is subject to geopolitical tensions that arise from disagreements or conflicts between countries. In this PESTEL analysis case, some of such tensions come with sanctions and bans, including a complete ban of Netflix’s streaming services. Also, for political reasons, governments may censor and limit access to some entertainment content from the company. These external factors are threats relevant to this PESTLE analysis of Netflix. Bans and censorship can reduce the company’s market share. On the other hand, political support for national promotion aims to encourage the popularization of content from various countries. In this PESTEL analysis case, such promotion in film is a political factor that offers Netflix the opportunity to distribute movies and series from various countries while making its streaming service more attractive to an international audience.

Economic Factors in Netflix’s Business

Economic trends and conditions are assessed in this component of the PESTEL analysis. The following economic factors affect Netflix:

• Higher purchasing capacity (opportunity)
• High inflation in some markets (opportunity and threat)

The economic development of countries, especially high-growth markets, comes with customers’ higher purchasing capacity for services, like Netflix’s. In this PESTLE analysis case, higher purchasing capacity is an external factor that gives the company an opportunity to grow its revenues and profits. For example, raising subscription fees in high-growth markets may improve Netflix’s profits from its international operations, although competition and customers’ price sensitivity may prevent the company from doing so. High inflation in some markets is another economic factor relevant to this PESTEL analysis of Netflix. This external factor is an opportunity because it can encourage customers to shift to online streaming, which is more affordable than going to cinemas. However, high inflation can also lead to an increase in subscription cancellations. Considering economic factors in this PESTLE analysis, Netflix’s competitive strategy and growth strategies ensure cost advantages that lead to the affordability of the company’s services, which supports competitiveness and profitable performance despite inflation-related limits in subscribers’ entertainment consumption.

Social/Sociocultural Factors

This component of the PESTLE analysis considers the social conditions that influence Netflix’s workers, customers, and business performance. The following are the sociocultural/social factors relevant to Netflix:

• Rising interest in multicultural content (opportunity)
• Strong regionalism in some markets (opportunity and threat)
• Increasing consumption of movie and series clips on social media (threat)

Netflix distributes content from various countries to address rising interest in multicultural content, which is an opportunity in this PESTEL analysis. Regionalism threatens the company by reducing demand for some types of content in some countries. However, regionalism is also an opportunity in this PESTLE analysis of Netflix, in terms of how content delivery can enhance customer experience. For example, the company can improve its fine-tuning of content suggestions to make viewers more satisfied despite the issue of regionalism. Content production for the trends of multiculturalism and regionalism supports the global entertainment goals of Netflix’s mission and vision . On the other hand, the consumption of clips of movies and series on social media is a strategic challenge relevant to this PESTEL analysis case. This external factor attracts audiences to view multiple clips to completely watch movies and series for free on social media instead of paying Netflix for the same content. Despite limited options in addressing this issue, aligning the qualities, core values, and traits of Netflix’s organizational culture (business culture) to the market’s social condition considered in this PESTEL analysis can provide insights into strategies that maximize social acceptance and demand for the company’s streaming service and original movies, series, and games.

Technological Factors influencing Netflix

Technologies and technological trends are assessed in this component of the PESTEL analysis. The following technological factors influence Netflix:

• Widespread use of mobile devices (opportunity)
• Improving internet connectivity worldwide (opportunity)
• Improving animation software capabilities (opportunity)

The widespread use of mobile devices worldwide is considered an opportunity in this PESTLE analysis case, such as for targeting demand for products specific to mobile devices. In this regard, the SWOT analysis of Netflix identifies product development and diversification as opportunities to use competitive advantages to provide new products, including more games for mobile devices. On the other hand, improving internet connectivity around the world gives opportunities for effective streaming services and improved customer satisfaction. In this PESTEL analysis of Netflix, this external factor can help retain customers, grow the business, and increase revenues. Moreover, the company can enhance its operations based on improving animation software capabilities. This technological factor is an opportunity in this PESTLE analysis case, in terms of how it increases the quality of Netflix’s animated content and subscribers’ satisfaction.

Environmental/Ecological Factors

This component of the PESTLE analysis assesses ecological trends or factors pertaining to the natural environment and its effect on business. The following are the ecological/environmental factors that affect Netflix:

• Increasing availability of renewable energy (opportunity)
• Increasing focus on sustainability (opportunity)

Netflix distributes its digital products through the internet. As a result, the ecological factors relevant to this PESTEL analysis mainly apply to the company’s office activities and film production and the operations of Amazon Web Services (AWS), which hosts Netflix’s content. For example, the increasing availability of renewable energy offers the opportunity to reduce the carbon footprint of the company’s movie production operations by using energy efficient equipment. Also, the increasing focus on sustainability is an opportunity in this PESTLE analysis of Netflix. The company can enhance its sustainability while encouraging subscribers to adopt more sustainable lifestyles. Netflix’s strategy for CSR/ESG and goals for sustainability and corporate citizenship are designed to enhance the business while accounting for these external factors and environmental trends in this PESTEL analysis case.

Legal Factors in Netflix’s Business Environment

Laws and regulatory trends are considered in this component of the PESTEL analysis. The following legal factors are relevant to Netflix:

• Improving regulations on intellectual property (opportunity)
• Protectionist regulation of media and entertainment (opportunity and threat)
• Lawsuits involving various parties (threat)

Netflix benefits from improving legal and regulatory protection for intellectual property. This external factor is an opportunity in this PESTLE analysis, referring to support for further production of movies, series, and games, with decreasing concern for intellectual property violations, like content piracy. However, some countries have protectionist policies that limit the external influence of online service companies, like Netflix. This legal factor can reduce content availability and make the streaming service less attractive to some audiences. Nonetheless, protectionist regulation is also an opportunity in this PESTEL analysis of Netflix. For example, business strategies can optimize content availability to attract audiences despite regulatory restrictions on content availability. Moreover, considering protectionism in this component of the PESTLE analysis, the promotional strategies and tactics in Netflix’s marketing mix (4P) can help mitigate this threat by attracting new subscribers to allowed content. Still, the company’s strategies need to account for lawsuits against its operations. These lawsuits may involve shareholders, governments, subscribers, and other parties. In this PESTLE analysis case of Netflix, such lawsuits are an external factor common among large multinational companies with online operations.

Recommendations – Netflix PESTLE/PESTEL Analysis

Recommendations based on external factors in this PESTLE/PESTEL analysis of Netflix focus on mitigating the effects of threats and capitalizing on opportunities in the industry and regional markets. The PESTEL factors provide various opportunities for growing the entertainment and streaming business. The following recommendations support international business growth despite the strategic challenges associated with the external factors in this PESTEL/PESTLE analysis of Netflix:

• Grow content production operations for movies, series, and games, based on economic, social, and technological factors and opportunities.
• Enhance Netflix’s marketing strategies to mitigate the limiting effects of political, social, and legal factors and threats.
• Develop consumer electronics to complement existing operations, especially gaming, to address external factors, particularly technological and legal opportunities and threats.
• Improve Netflix’s business sustainability and the sustainability of business partners and suppliers, to account for environmental or ecological trends.
• Asmar, A., Raats, T., & Van Audenhove, L. (2023). Streaming difference(s): Netflix and the branding of diversity. Critical Studies in Television, 18 (1), 24-40.
• Davis, S. (2023). What is Netflix imperialism? Interrogating the monopoly aspirations of the ‘World’s largest television network’. Information, Communication & Society, 26 (6), 1143-1158.
• Netflix, Inc. – Form 10-K .
• Netflix, Inc. – Long-Term View .
• Phan, S. (2021). The effect of PESTLE factors on development of e-commerce. International Journal of Data and Network Science, 5 (1), 37-42.
• Schaffner, B., Stefanescu, A., Campili, O., & Chetty, M. (2023). Don’t let Netflix drive the bus: User’s sense of agency over time and content choice on Netflix. Proceedings of the ACM on Human-Computer Interaction, 7 (CSCW1), 1-32.
• U.S. Department of Commerce – International Trade Administration – Media and Entertainment Industry .
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Inflation Case Studies Samples For Students

62 samples of this type

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Example Of Strategic Corporate Finance Case Study

- Worksheet entry figures

Cash flow figures and adjustments:

The price used for sales estimation is the £50/MWh tariff that is guaranteed by the government. On the other hand, the megawatts used for the two projects over the 15years period include 60,000 MWh for the small wind-farm and 120,000 MWh for the large wind-farm project.

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Good case study about inflation and debt, introduction.

This paper is based on the discussion of the article “Inflation and Debt’ by John Cochrane. In this paper, different concept presented in the paper will be presented and discussed. One of the concepts, discussed in the paper, is inflation. The central question related to inflation is the value of paper money. It is argued that the paper has money because the government accepts currency in the form of tax payments. The retailers and service provides charge money on their products and services because they are required to pay taxes (Barney, Dwayne, and Harvey pp. 97).

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GDPreal2001=GDPnominal2001*100GDP deflator2001=10128*100102.4≈9890.6

The real GDP for 2002 can be calculated using GDP growth rate:

GDP growth ratet=GDPt-GDPt-1GDPt-1*100% 1.6%= GDPreal2002-9890.69890.6*100 → GDPreal2002≈10048.8

The formula for calculating the growth rate of GDP used in (a) is applicable here:

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The production director of Wilmslow Ltd wants to schedule production for quarter 3 (the twelve weeks ending 17 September) and asks you to use the revised information to prepare the following: - The revised production budget for Alphas and Betas;

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Here's where the middle class is experiencing the best — and worst — standard of living

By Aimee Picchi

November 22, 2023 / 4:03 PM EST / MoneyWatch

Middle- and working-class families are enjoying the best standard of living in some of the most expensive U.S. cities, according to a new economic analysis. 

That may seem far-fetched given that people earning less than $100,000 in San Francisco are considered low income , but the new analysis from the Ludwig Institute for Shared Economic Prosperity (LISEP) found that the high cost of living in these regions is offset by higher-than-typical wages.

In fact, the best performing region for middle- and working-class families is the Bay Area, despite the sky-high cost of living in San Jose and San Francisco, according to the analysis of 50 big U.S. cities.

Even so, about 6 in 10 Americans are failing to meet their basic needs, with their incomes falling short by almost $14,000 on average in 2022, LISEP noted. That underscores the struggles that many households are facing after two years of rising inflation, which has pushed up costs for everything from food to rent. 

"For middle- and lower-income Americans, wherever it is in the United States, you aren't doing great," Gene Ludwig, the chairman of LISEP, told CBS MoneyWatch. 

Examining the intersection of wages and the cost of living at a regional level is important because "we all live locally," Ludwig noted.

Even though the cost of living in the Bay Area is among the highest in the U.S., the region offers a more diverse mix of jobs, including a bigger range of upper-middle-income jobs, than some other cities. But cities where median household incomes are failing to keep up have sparser opportunities, by comparison. 

In cities such as Las Vegas and Fresno, "It means there are more low-wage and middle-income jobs than there are upper-paying middle-income jobs," Ludwig noted.

The analysis was based on city-specific data including the cost of living for households, examining essential items such as housing and food, as well as earnings for full- and part-time workers, as well as for jobless people who are seeking employment. 

The unequal impact of inflation 

Ludwig, the former comptroller of the currency and the founder of Promontory Financial Group, created LISEP in 2019 to track economic measures of well-being for middle- and working-class Americans, such as wages and unemployment. 

While the U.S. government tracks such data, Ludwig argues that the measures often don't accurately reflect the economic situation for millions of U.S. households — including the impact of inflation, which is a sore point for many Americans after two years of bruising price hikes.

Inflation has hit low- and middle-class Americans particularly hard, something the Consumer Price Index — the national measure of inflation — isn't capturing, Ludwig noted. That's because the CPI, a basket of goods and services, tracks some items that may not have much bearing on the lives of middle-class families, and thus doesn't accurately reflect their experiences, he added. 

Housing as measured by the CPI has increased 54%, but Ludwig's group's analysis found that the typical rent for middle- and lower-income households has soared by almost three times that level, at 149%. 

"In the last 20 years, inflation for middle- and lower-income Americans has been higher than it has been for upper-income Americans," Ludwig said. "Wage growth hasn't kept pace such that you are worse off than you were 20 years ago." 

Sharing the wealth generated from a growing U.S. economy is essential to maintaining the middle class and creating a stable society, he added. That can help middle- and low-income Americans "share in the American dream," Ludwig said. "Unfortunately, it's going in the wrong direction."

Aimee Picchi is the associate managing editor for CBS MoneyWatch, where she covers business and personal finance. She previously worked at Bloomberg News and has written for national news outlets including USA Today and Consumer Reports.

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The uncomfortable truth about record high immigration levels, rents and inflation

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Breaking news.

Former US secretary of state Henry Kissinger has died aged 100

Analysis The uncomfortable truth about record high immigration levels, rents and inflation

You could call them the four "I"s of our economy. And they've now collided in spectacular fashion.

Almost all of us have been obsessed by just two: inflation and its impact on interest rates.

But there are another two that need to be brought into the equation: immigration and the need for infrastructure.

Every economist, from Reserve Bank governor Michele Bullock down, admits that interest rates are a blunt weapon that disproportionately affects different segments of Australian society, particularly younger Australians who bought real estate in the past three years.

But for a large number of economists, it is the only weapon. Many refuse to even consider alternatives, primarily because they shy away from a debate that has become socially and, occasionally, racially charged. And yet, they're often more than happy to continue to push for ever higher interest rates.

In the past fortnight, inflation pressures eased substantially in both the United States and the United Kingdom. While it is declining here, it is at a much slower pace than the RBA would like , which forced it to raise rates on Melbourne Cup Day.

That's provided ammo to the hawks, who've bolstered their calls for even more rate hikes. And last week, the federal government announced it would take a scythe to infrastructure spending in a bid to relieve inflation pressures following prompts from the International Monetary Fund.

That IMF report also pumps for more rate hikes . But like many others, while it acknowledges the root cause of our high inflation, it doesn't consider the obvious solution and skirts the fundamental problem.

"Rents have also increased at a very fast pace, with strong growth in immigration following the post-COVID re-opening adding to pressures, given the housing shortages," it notes.

A homegrown crisis

We are in the midst of a full-blown rental crisis.

Just on a third of all Australian households rent and many are finding it difficult to keep their head above water. These are the forgotten victims of the most recent onslaught of higher interest rates and super-charged living costs.

Rents have been soaring for most of the past year and vacancy rates, at just 1.1 per cent across the nation, according to property data firm PropTrack, are now at their lowest levels in history.

Our immigration intake, meanwhile, is running at record levels with up to 600,000 arrivals expected this calendar year. If we continued at that rate for four years, there'd be enough people to fill a city the size of Brisbane.

And here's another little snippet highlighted by the most recent inflation data from the Australian Bureau of Statistics: Rents now are growing at their fastest pace in 14 years and are a key factor driving our inflation.

According to the ABS, rents account for about 6 per cent of the Consumer Price Index, making it the second-largest contributor to the index.

"Understanding the rental market is important for policymakers as it has implications for patterns of consumption and savings by households, as well as inflation," it warned back in April .

And yet, despite the overwhelming evidence, few appear willing to confront one of the key forces driving inflation.

Rather than whack everyone with ever higher interest rates because rents are going crazy, wouldn't it make more sense to simply scale back the level of immigration, even temporarily, to take the pressure off rents and help lower inflation?

All those people arriving need somewhere to live and the increased demand is driving rents higher.

It's a problem likely to compound into the future.

It takes years to build a house or a block of units. Then consider that vast numbers of builders have gone bust and that new dwelling approvals have this year slumped to decade lows partly because of soaring interest rates.

This is not, and should not be, an argument about immigration, multiculturalism, race or diversity. It's an issue that revolves around simple arithmetic.

The IMF strikes again

The IMF is a textbook case of how intelligent individuals become consumed by textbook solutions to real-world problems. Who could forget its disastrous stipulation to nations left impoverished by the Global Financial Crisis to embark upon austerity programs?

Its report on Australia a fortnight ago neatly glosses over the nub of the issue. Rather than suggest scaling back the intake of new arrivals, it instead proposes to scale back on the necessary infrastructure needed to accommodate those new arrivals.

"The Commonwealth Government and state and territory governments should implement public investment projects at a more measured and co-ordinated pace, given supply constraints, to alleviate inflationary pressures," it wrote.

One of the biggest problems we've faced since the turn of the century is that our politicians have been more than happy to import people but they've been unwilling to spend the required money on ensuring our cities work properly.

For decades, until COVID hit, we used to boast about being the miracle economy. No recession in 30 years! Technically, it was true. Our GDP climbed each and every year. But it was off the back of one of the biggest immigration programs in the developed world. Adding more people adds to the size of your economy.

Without the necessary extra investment in transport, health and education, however, our cities became more difficult to traverse, reducing worker productivity, and became some of the most expensive places in the world in which to live.

When the September-quarter GDP figures lob, they're likely to show that without immigration, the economy would already be in recession.

While the IMF may have a legitimate argument that we should be more sensible about infrastructure spending, that can't be achieved with immigration rates running at twice the normal level.

Can rate hikes lower rent?

Immigration in the post-war era has transformed Australia into a vibrant society with an array of rich cultural heritages from across the region and around the globe.

From a social cohesion viewpoint, the program has been an outstanding success.

For it to continue to work, governments both state and federal need to address the structural issues that arise from a rapidly increasing population.

Housing is one of the paramount issues.

Trying to pretend there is only a loose relationship between the huge lift in immigration and the sudden increase in rents — which is fuelling inflation — is likely to create more serious social problems in the future.

It's a problem that won't be fixed by yet another hike in interest rates.

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Journal of Corporation Law

Aggregated risks in mutual fund disclosures.

Scholars have roundly criticized compulsory consumer disclosure over the past decade for good reason. Disclosures, whether describing the terms of a loan or the risks of investing, purport to inform consumers. But who actually reads disclosures? We argue that mutual fund disclosures are different. Unlike other consumer-facing disclosures, mutual fund disclosures are dynamic and, therefore, informative. The Securities and Exchange Commission (SEC) requires funds to report changing market conditions that affect a fund’s investments. As a result, aggregated risk statements provide information about new and evolving risks over and above insights from any single risk disclosure. But disclosures’ utility comes not from their superior ability to inform the ordinary investor. Rather, we propose that fund disclosures’ true value lies in what they can tell regulators about funds’ perception of market risks in the aggregate. We evaluate our thesis through an analysis of all U.S. mutual funds’ narrative risk disclosures from 2011 through 2022. We leverage social science theories of risk and uncertainty to conceptualize and operationalize the choices funds make in depicting changing market conditions. We locate these risks and uncertainties along a distribution from common and manageable to uncommon and catastrophic. We then assess funds’ disclosure of changing market conditions using a “most likely” case design by examining funds’ disclosure of increasing inflation, public health crises, and severe weather events resulting from climate change. Each case study presents either a risk—meaning that the universe of bad outcomes is known and can be accounted for—or uncertainty—meaning that the universe of outcomes is unknown and cannot be meaningfully estimated. We find that, in the aggregate, funds reconceptualize and adjust their disclosures in response to external events. Disclosure topics and language move in predictable and statistically significant ways. Changes in disclosure language are, in fact, meaningful. Such a response, when taken as a whole, provides insight into funds’ perception of risk. Our findings suggest that quantitative text analysis can help the SEC assess overall fund compliance with disclosure mandates. But it can also help regulators, market participants, and researchers better understand changing risk environments.

• Volume 49, Number 1
• Tech Supremacy: The New Arms Race Between China and the United States
• Out with Fiduciary Out?
• Shining a Light on Shadow Banks
• Delaware Law Requires Directors to Manage the Corporation for the Benefit of its Stockholders and the Absurdity of Denying It: Reflections on Professor Bainbridge’s Why We Should Keep Teaching Dodge v. Ford Motor Co.
• Directions for U.S. International Tax Policy, A Response to Hanna and Wilson
• Systematic Stewardship: It’s Up to the Shareholders—A Response to Profs. Kahan and Rock
• Delaware Law for Non-Corporate Entities: A Commentary
• Venture Predation
• Returning Markets to the Center of Corporate Law
• Voting on Reporting
• Initiation Payments
• Dual-Class Shares in the Age of Common Ownership
• The Separation of Ownership and Conscience
• Systemic Stewardship with Tradeoffs
• Opportunism in the Shareholder Voting and Engagement of the “Big Three” Investment Advisers to Index Fund
• How Fatal Ambiguity Undermines Effective Insider Trading Reform
• The Irrelevance of Delaware Corporate Law
• U.S. International Tax Policy and Corporate America
• China and the Rise of Law-Proof Insiders
• Why We Should Keep Teaching Dodge v. Ford Motor Co.
• TO CALL A DONKEY A RACEHORSE — THE FIDUCIARY DUTY MISNOMER IN CORPORATE AND SECURITIES LAW
• Max Oversight Duties: How Boeing Signifies a Shift in Corporate Law
• The Perils and Questionable Promise of ESG-Based Compensation
• Maximal Accountability with Minimally Sufficient Punishment
• Crime and the Corporation: Making the Punishment Fit the Corporation
• Corporate Coverture
• Is the Corporate Criminal Enforcement Ecosystem Defensible?
• What Rises from the Ashes?

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Climate crisis and energy costs fuel £600 rise in UK household food bill, analysis finds

Extreme weather contributing one-third of all food price inflation with worse to come in 2024, warn climate researchers

British households’ food bills have been driven up by more than £600 over the past two years by the global climate emergency and soaring energy prices, according to a report warning of further increases to come in 2024.

Sounding the alarm over the impact from increasing extreme weather patterns for food production, the Energy and Climate Intelligence Unit (ECIU) thinktank said that global heating was directly contributing to the cost of living crisis.

According to the analysis carried out by researchers from the universities of Bournemouth, Exeter and Sheffield, more extreme or unseasonal weather accounted for one-third of all food price inflation in the UK this year.

Combined with the impact of soaring energy prices – after Russia’s invasion of Ukraine drove up gas, energy and fertiliser prices – it said British households had been hit by £605 in additional food costs in 2022 and 2023. While energy prices have fallen back this year, it warned that the impact from the climate emergency was increasing.

Tom Lancaster, land analyst at ECIU, said: “Climate change is playing havoc with global food production, and this is inevitably feeding through to higher prices at the tills. Across 2022 and 2023, the climate emergency alone added the equivalent of six weekly shops to the average household food bill.”

The cost of the climate crisis rose from £171 in 2022 to £192 in 2023, more than offsetting the effects of falling energy prices this year and having a greater impact than rising energy bills, according to analysis.

Official figures show inflation in food and drink prices peaked at an annual rate of almost 20% earlier this year, the highest level since the 1970s, amid disruption to food supplies from weather events and soaring energy costs for producers.

Food price inflation has fallen back in recent months, but remains at historical highs of close to 10%. Prices are also still near record highs after recent storms – including Storm Babet – flooded swathes of farmland, hitting UK potato and vegetable harvests in the run-up to Christmas.

In 2022, drought hit production of basic foodstuffs such as potatoes and onions in the UK, followed by an unusually wet harvest in 2023, and then the hottest September on record.

It comes after heatwaves across the Mediterranean, India and South America this year all had a major impact on food production and prices. Staples including sugar, rice and tomatoes were affected by extreme weather, such as droughts in India, while olive oil rose in price by 50% after two years of drought and heatwaves in Spain and other major exporters in southern Europe.

The situation could be worse next year with the El Niño weather system leading possibly to more severe weather and further increases in food prices.

Prof Wyn Morgan of Sheffield University, one of the report authors, said: “Given we expect climate impacts to get worse, it is likely that climate change will continue to fuel a cost of living crisis for the foreseeable future.”

Anna Taylor, executive director at the Food Foundation, said that the government needed to “think more seriously how households can become more resilient to price volatility” in the light of the likely impact of the climate crisis.

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She called on the government to revive its plans for a horticulture strategy that would build production of fruit and vegetables in the UK and reduce reliance on crops grown in southern Europe which is becoming increasingly vulnerable to drought and extreme heat as a result of the climate crisis.

A separate report from the Food Foundation warned that retailers and hospitality venues in Britain were failing to create a food environment where healthy choices are affordable, readily available and appealing.

It found healthy food was already twice as expensive as unhealthy food per calorie, while the cost of sustainable alternatives to meat and dairy can also be high.

Most main meals offered by many pub chains regularly exceed 50% of the recommended daily intake for calories, saturated fat, salt and sugar, according to the report. Meanwhile, just 1% of food advertising spend goes towards fruit and vegetables compared with 9% on meat and dairy while 21.5% of buy-one-get-one-free deals are on meat and dairy compared with just 4.5% on fruit and vegetables.

Lancaster said that the dependence of the UK’s current farming system on volatile oil, gas and fertiliser prices had created a “perfect storm of extreme weather, high gas prices and global instability” to food price inflation.

He said: “The good news is that steps to make farming more sustainable cannot only cut emissions but also make our food production more resilient to the extremes of flooding and drought. Government plans in England to support greener farming with more hedgerows, improved soil health and tree planting schemes are therefore vital to our future food security.”

• UK cost of living crisis
• Extreme weather
• Extreme heat
• Food & drink industry
• Climate crisis

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