Abstract
The present study examines the decomposition of relative price variability into two components (i.e., inflationary and real factors) in India using monthly data on 105 commodities prices over the period January 2005 to March 2017. The analysis of the study revealed that under primary food articles, 53% of relative price variability is due to real factors, and the remaining 47% due to inflationary factors. Whereas for manufactured food products, 30% of relative price variability is due to real factors, and the rest of the 70% due to inflationary factors. Overall, the important conclusion that emerges from the analysis is that few commodity prices have a larger contribution to relative price variability in the food basket. The majority of commodity prices under primary food articles have a larger contribution to variability in relative price changes, whereas under manufactured food products have the least contribution. Moreover, this study also accounts for wholesale price index and consumer price index non-food commodities to identify to which extent relative price variability is determined by real and inflationary factors.
Introduction
Over the past few decades, a rapid increase in food inflation has created serious concern among the government authorities and policymakers across the world. It hampers the welfare of the country by increasing the infant and child mortality of the nation. Notably, the world has experienced food inflation shocks during 2007–2008, 2010–2011 and 2013 due to certain reasons. Walsh (2011) argued that food inflation is more explosive and higher than non-food inflation in lower-income countries, and persistent rise in food prices is transmitted to non-food inflation in many countries. One of the major problems in inflation targeting is high inflation pressure, which originated from food prices. In fact, food inflation is not only creating a problem for overall inflation, but also creating difficulties in the forecasting accuracy of the inflation targeting process (Šoškić, 2015). Food price inflation plays a significant role in the inflation dynamics and policy point of view of central banks, particularly for inflation-targeting countries. The rising importance of food price inflation contributed to a larger share in total household spending.
However, the impact of food prices on inflation varies across countries. Because it depends on economic development, the contribution of food in the aggregate consumer price index (CPI) basket, and the level of income of the country. Therefore, the rise in food prices may adversely affect poor consumers in developing countries, especially India, where most consumers spend their larger portion of income on food products. One of the major macroeconomic challenges that have been faced by India is to control food inflation pressures. The rising food price inflation is considered as one of the key contributors to the increase in overall wholesale price index (WPI) inflation in India (Anand et al., 2014). Because, the weight of food comprises nearly 40% and 25% in India’s CPI and WPI, respectively. The average WPI food price inflation was recorded at 8%, whereas non-food inflation was observed at 4% during January 2006 to March 2017 (Office of Economic Advisor, 2017). The inflation in primary food articles has started increasing in 2006 and peaked at 21.85% in May 2010 and finally reached 19.69% in December 2013. Similarly, inflation rate of manufactured food products was significantly high at 10.43% and 19.30% in July 2008 and March 2010, respectively, and again reached 12.60% in June 2016. The primary reason behind the high inflation rate (10.9%) of all commodities in May 2010 was high food inflation. The changes in the relative price of food items play a central character in the demand and supply. Therefore, the central bank should pay attention to food price inflation while targeting overall inflation for the country at large.
The rising relative price variability occurs due to both inflationary factors (supply side) and real factors (demand side). However, there has been a long debate on the effects of inflation on the relative price variability in the literature, which can be associated with market behaviour. The theory of inflation and relative price variability is based on the menu cost approach and rational expectation model. Inflation has an adverse effect on the real sector of the economy through its relative price variability. 1 Under the menu cost model, when a higher inflation level prevails, changes in prices become more scattered. Hence, larger variability in relative price changes (Sheshinski & Weiss, 1977). Ball and Mankiw (1995) argued that large shocks to a few commodities have a disproportionate effect on aggregate inflation due to the firms’ price adjustment. Hence, the distribution of relative price changes promotes aggregate inflation. Further, Ukoha (2007) suggests that high inflation will increase relative price variability among the agriculture commodities, in turn, inefficient and misallocation of agriculture resources. Whereas, under the rational expectation model, the rise in unexpected demand, which creates inflation, will tend to rise in relative prices (Barro, 1976; Lucas, 1973). However, along with inflationary factors (supply side), such as changes in technology, resource availability, and other factors of supply, variability in relative price is also originated from real factors, namely, real income, family composition, and various other factors of demand (Parks, 1978; Rather et al., 2014).
There has been a growing importance of decomposition of relative price changes over the period as inflation affects real sectors through the relative price changes. Suppose relative price changes occur due to real factors that lead to an efficient allocation of resources because these forces arise from market forces of the economy. On the other hand, if variability in relative prices changes arises due to inflation, it decreases the economic welfare benefits in the economy by an inefficient allocation of resources and agricultural sectors in particular. Therefore, it is essential to know at which magnitude relative price changes is determined by inflationary (supply side) and real factors (demand side) in the variability in relative price changes. This will provide useful insights for the policy makers to implement policy decisions regarding the responsible commodities of higher variability in relative price and forecast inflation accurately. The quantifying relative importance of both demand and supply-side factors would give an idea of specific policy suggestions regarding demand and supply to tame the high relative price of the food basket. This study can also offer some policy initiatives relating to disaggregated commodities on how changes in the relative price of a particular commodity can affect the economy’s stability, followed by the welfare of the people to a larger extent.
The study makes various significant input to the literature in several ways: first, numerous studies have conducted to understand, causes and cures of food price inflation in India (Bhattacharya et al., 2014; Gokarn, 2010; Gulati & Saini, 2013; Huria and Pathania, 2018; Rajan, 2014) and different researchers have given their different conclusions regarding trace the reasons for higher food price. 2 The common features of their studies have mainly restricted to only the nature of food inflation, and most of the studies are primarily confined to supply-side factors. However, the relative importance of demand and supply-side factors towards relative price changes of food items have not been considered in their studies. Second, the study identifies the each of commodity prices, which contributes to the variability of relative price. It also examines to what extent variability in relative price is caused by real factors (demand side) and inflationary factors (supply side). Third, a little study has recognized the commodities that led to variability in relative price changes in the food basket using different data periods and methodology. However, we have covered a larger number of commodities at the disaggregated level, longer time period, and Clements and Nguyen (1981, 1982) methodology for decomposition analysis in our study. Fourth, few studies have investigated the decomposition of relative price variability for the aggregate price level, namely, Clements and Nguyen (1981, 1982) for Australia, Ram (1990) for the USA and Rather et al. (2014) for India. However, none of the studies have explored the decomposition of relative price variability of food items in India. Fifth, this study also reflects on verifying to what extent non-food (both WPI and CPI) commodities are accountable in the variability of relative price changes of food items. Finally, to the best of our knowledge, this is the first study investigating the decomposition of relative price variability into two components due to real factors and inflationary factors. Therefore, this study accomplishes the gap in the existing literature.
The remaining of the article is organized as follows. The second section provides a brief review of the literature of the related studies. The third section outlines data and methodology. The fourth section presents primary analysis. The fifth section presents the empirical results and discussion. Finally, the sixth section provides conclusions and policy implications of the study.
Review of Literature
Inflation and Relative Price Variability
The relationship between inflation and relative price variability is not new, and a large number of studies have investigated the nexus between these two across the world. However, the effects of inflation on relative price variability for agricultural commodities are scarce. In particular, developing countries like India where a large section of people spends their larger portion of income on food and also contribute a leading share to overall inflation in WPI and CPI. The changes in the relative price of the food items may hamper the welfare of the country.
For instance, Parks (1978) examined the impact of unanticipated inflation and real income on the variance of relative price changes in the Netherlands and the USA during 1921–1963 and 1929–1975, respectively. His results showed that unanticipated inflation is positively impacted the variance of relative price changes. Clements and Nguyen (1981) investigated the effects of inflation on variance in relative price changes in Australia for seven commodity groups during 1959–1978. The results showed that past inflation in rent is identified as the variation in relative price changes. However, the current inflation drives relative price variability in cigarettes, rent and others. Further, the impact of inflation on relative price variability for food, cigarettes, etc., and motor vehicles is positive. Clements and Nguyen (1982) examined the relationship between inflation and relative price in Australia using decomposition analysis over the period 1959–1978. The author found that 76% of the variability in relative prices is determined by real factors. However, 24% of the variability in relative price is determined by inflationary factors. Further, they also revealed that 43% of overall relative price variability is contributed by clothing only. Ram (1990) demonstrated that real factors and inflationary factors are equally responsible for the variability of relative price in the USA. Ghauri et al. (2014) analysed the impact of unanticipated inflation (supply side) and real income (demand side) on relative price variability in Pakistan, covering the period from July 2001 to June 2011. Their findings of the study revealed that the supply-side factors drive relative price variability. However, the demand-side factor fails to determine relative price variability. However, Rather et al. (2014) revealed that inflation has a positive impact on relative price variability. Further, the authors also found that the relative price variability is determined by both real and inflationary factors. However, a higher proportion of relative price variability is derived from real factors.
However, few studies have focussed on the relationship between inflation and relative price variability of food items. For instance, Lach and Tsiddon (1992) analysed the effects of inflation on the dispersion of prices utilizing disaggregated data on 26 foodstuffs in Israel, spanning, January 1978 to September 1984. The study results found that intra-market relative price variability has resulted from the expected inflation rather than unexpected inflation. Lapp and Smith (1992) investigated the effects of macroeconomic instability on relative price variability for 47 agricultural commodities in the USA over the period 1962–1987. Their finding revealed that unanticipated inflation was found to be positive with the variation in relative price changes. However, contrary to this, Smith and Lapp (1993) found that the actual inflation positively impacts relative price variability in agriculture rather than unexpected inflation in the UK over the period 1956–1988. Loy and Weaver (1998) examined the relationship between anticipated and unanticipated inflation and relative agricultural price volatility in Russian food markets during January 1993 to December 1995. The results of the study showed that the anticipated inflation rate drove variability in relative prices. Rezit (2005) studied the change in relative price variability is positively induced by inflation rate changes and economic activity among 53 agricultural commodities. Ukoha (2007) investigated the impacts of inflation on relative price variability among agricultural commodities in Nigeria during 1970–2003. He found that the effects of inflation on relative price variability of agricultural commodities are positive and significant in both the short- and the long run. Baek (2010) also argued that changes in inflation have a positive impact on relative price variability across US food products.
From the above literature review, we conclude that numerous studies have focussed on factors responsible for high food price inflation in worldwide. The basic idea of these studies is mainly constrained to only the nature of food inflation, and mostly confined to supply-side factors. However, the relative importance of demand and supply-side factors towards relative price variability has not been considered. Hence, it is essential to inspect the extent to which relative price variability is caused due to real (demand side) and inflationary (supply side) factors. To the best of our knowledge, none of the studies have investigated the decomposition of relative price variability for the basket in terms of food inflation into two components due to real factors and inflationary factors. Therefore, this study aims to inspect the decomposition of relative price variability in India.
Data and Methodology
Data
The present article uses of monthly data on 105 commodities prices, which represents 23% of WPI in India. There are 112 numbers of commodities included in primary food articles and manufactured food products (2004–2005 base year). 3 Due to the lack of historically comparable data on the all-India CPI commodity-wise food items over the period, we have used the WPI disaggregated data during January 2005 to March 2017. Further, in order to check robustness on CPI disaggregated data, we have used the available data during January 2014 to February 2020. 4 Further, to verify to what extent non-food items contribute variability of relative price changes of food items, we included WPI and CPI non-food commodities. 5 The data period selection has been considered based on the availability of uniform and consistent data on the price of commodities over the period of time. We have also constructed an index for food inflation using the weighted least square of both primary food articles and manufactured food products using WPI indices. The data on WPI food and non-food price indices and their weights, and CPI food and non-food indices and their weights are retrieved from the Office of the Economic Adviser, published by the Ministry of Commerce and Industry and Consumer Price Indices Warehouses, Ministry of Statistics and Programmes Implementations, respectively. However, the data on consumer price index for industrial workers’ food (CPI-IW) are collected from the Labour Bureau.
Methodology
In order to decompose relative price variability into two components, that is, due to real factors and inflationary factors, we have used the technique developed by Clements and Nguyen (1981, 1982). The essence of present technique is to identify which commodity share has higher relative price variability of food basket. It also helps figure out the relative influence of individual commodity in the variability of relative price and identify in which magnitudes it is affected by inflationary factors and real factors.
The study has used the ordinary least square method to estimate the α and β for 105 commodities using the equation
Measurement of Relative Price Variability
Suppose,
where
where
When, prices of all the commodities are proportional, then
where
where
Decomposition of Relative Price Variability of Food Items
The share of commodity i in
where
Both
which can be either positive or negative. The total share of real changes in
and the share of due to inflationary factors in
and interaction component of both real and inflationary share in
Hence,
The average share of real, inflation and interaction component in relative price variability over the period can be defined, respectively, as:
where T is the time. The average share of ith commodity in relative price variability is interpreted as:
Similarly, the contribution of the average share of real, inflation, and interaction component of
Preliminary Analysis
Food Inflation and Distribution of Relative Price Variability
Descriptive Statistics.
Additionally, we have also represented the graph of food price inflation and relative price variability to understand the association between the variables, which is shown in Figure 1. The high relative price variability is observed when food inflation is high. Inflation encourages variation in relative price variability. The results of disaggregated food items also exposed that variation in very few commodities creates a high fluctuation in the whole relative price variability.

Empirical Analysis
Shares of Commodity Prices in Relative Price Variability
Sector-wise Contribution to Relative Price Variability of Food Items.
Shares of Disaggregated Food Items and its Decomposition
Shares of Decomposed Commodities.
Shares of Wholesale Price Index Non-food and Its Decomposition
Shares of Commodity Prices and its Decomposition Analysis using WPI Non-food Data.
It is interesting to notice that proportion of real factors in the share of cotton shirts is found to be zero. However, the share of urea in the proportion of real factors seems negligible as 90% of the variation is due to inflationary factors. For sugarcane, 60% of the variability in relative price changes is due to real factors and 40% by inflationary factors. For high-speed diesel, 52% of the variability is initiated by real factors and 48% by inflationary factors. From the above analysis, it is clear that an increase in non-food items has contributed to higher relative price in food items as it implies upward pressure on input prices. Few non-food commodities lead to relative price changes, and most of them are attributed by inflationary factors. However, sugarcane, gold and gold ornaments and coking coal are determined by real factors.
Robustness Check
The food contributes higher weights, which accounts for nearly 39.8% of aggregate CPI basket whereas, 24.6% weights of aggregate WPI basket. Therefore, we use CPI disaggregated data to check the robustness of the study. The results are displayed in Table 5. The results are reported whose share is 2% or higher. It shows that 22 commodities have been identified among the 106 commodities, which contribute 94% of the variation in relative price changes. The results show that nine commodities are together contributing 83% of the variability in relative prices. However, among them, tomato determines 45% of the variability in relative price changes, followed by potato (10%), onion (9%), cauliflower (7%) and so on. It is also revealed that, in the case of tomato, 39% of relative price variability is attributed by real factors, and 61% is by inflation factors. For potatoes, 36% of the variation in relative price changes is due to real factors, and 64% of the variation is due to inflationary factors. However, for onion, 25% of fluctuation in relative prices is decided by real factors, and 75% by inflationary factors. Based on the above results, we found that most of the responsible commodities in the fluctuations of the relative price changes are identified as vegetables. The relative price variability of all the commodities is largely determined by inflationary factors and shared as highest against real factors except few items, like fish prawn and goat meat/mutton. Since food contributes significant weight (nearly 40%) to the CPI basket, it implies that any increase in food prices would surge the CPI inflation.
Shares of Commodity Prices and its Decomposition Analysis using CPI Food Data.
Shares of Commodity Prices and its Decomposition Analysis using CPI Non-food Data.
Shares of Commodity Prices and its Decomposition Analysis using CPI-IW Data.
From the CPI-C and CPI-IW analysis, we conclude that very few commodities are responsible for the higher variability in relative prices, and most of them are vegetables. The variability of identified items is due to both real and inflationary. However, inflationary factors contribute a larger variability in the relative prices in the food basket.
Comparison between WPI and CPI Results
First, few commodities are predominately contributing to larger variability in the relative price of food basket as a whole. Only 25 commodities contribute 93% of the relative price variability among 105 commodities from WPI data. Among them, cabbage alone provides 24% of the variability in relative price changes. However, from the CPI-C data, it is observed that 22 commodities have been identified among the 106 commodities, which contribute 94% of the variation in relative price. Among them, one commodity, namely, tomato, which determines 45% of the fluctuation in relative prices.
Second, the changes in relative price variability are mainly due to vegetable prices determined by both real and inflationary factors but magnitude is larger for inflationary factors for both the results. However, the variability in relative price changes in all the commodities are largely determined by inflationary factors and shared as highest against real factors except fish (prawn), parwal and goat meat/mutton from CPI results. Third, both the CPI and WPI non-food items are significantly responsible for the relative price variability of food items.
From the above analysis, we can conclude that the majority of identified commodities in relative price variability (mainly vegetables) are largely determined by inflationary factors form CPI results, whereas changes in relative price variability are mainly determined by both real and inflationary factors from the WPI results. However, inflationary factor has nearly 60% share in the relative price variability. Overall, the results obtained from both the data set exhibits similar results. However, it varies with magnitudes.
Conclusions and Policy Implications
The present study empirically investigates the decomposition of relative price variability in the case of India employing monthly frequency on 105 commodities prices, spanning the period January 2005 to March 2017. This study broadly focuses on three important issues: (a) identifying the individual commodities whose contribution is higher towards variability in relative prices; (b) investigating the decomposition of relative price variability into two components due to inflationary and real factors. For that, we have used the methodology developed by Clements and Nguyen (1981, 1982); and (c) checking the robustness of CPI food disaggregated data. We have also taken into account WPI and CPI non-food commodities to verify to what extent non-food commodities are accountable in relative price variability of food items.
Based on the empirical results, we found that only 25 among 105 commodities are predominately contributing 93% of the variation in relative price changes in the food basket. The decomposition analysis results indicate that 53% of the variability in the relative price of primary food articles is due to real factors, and the remaining 47% is due to inflationary factors. Whereas 30% of the relative price variability of manufactured food products is due to real factors, and the rest 70% is due to inflationary factors. Overall, the commodity having the highest share largely contributes to variability in relative price by both demand and supply-side factors. However, the inflationary factor contributes a relatively larger share in the variability in relative prices. In particular, higher relative price variability is mainly contributed by vegetable prices. The study concluded that few commodity prices have a larger contribution to the variability of relative price. The primary food articles have a higher contribution to relative price variability, whereas manufactured food products have the least contribution. Moreover, the CPI food results demonstrated that most of the food commodities in relative price variability are largely determined by inflationary factors. Finally, it is concluded that non-food items are also responsible for the variability of relative price changes of food items. Most of the commodities responsible for variability in relative price changes are from agricultural inputs like power and fuel.
Based on the empirical findings, we can draw the following policy implications. Our results concluded that both the supply- and demand-side factors are responsible for larger relative price variability, and robustness check results revealed that relative price variability is mainly due to inflationary factors (supply side). Therefore, the government and policymakers should take important policy measures for both the supply and demand sides. First, to meet the supply-side response, we need to increase the growth of agricultural productivity. Therefore, the government should take appropriate policy decisions to boost agricultural production and productivity via adopting new technology, investment in agriculture. Second, various institutional reforms, such as allocating different crop insurance schemes and providing rural credit facilities via rural banking and small-scale cooperative societies, should be taken by the government. Third, to meet the demand-side response, the contractionary monetary policy measures might help to curb the food price inflation by reducing the money supply and credit facilities, which eventually moderate consumption demand. Fourth, both food and non-food items are accounted for the variability of relative price changes of food items. Therefore, the central bank should take suitable policy decisions by focussing on commodity-wise disaggregated inflation points of view while targeting headline inflation to maintain stability in relative prices and growth of the economy. Finally, if variability in the relative price of both the identified food and non-food items can be checked by implementing an appropriate policy stance. In that case, food inflation can be eliminated as a whole term.
Footnotes
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Funding
The authors received no financial support for the research, authorship and/or publication of this article.
