Introduction
The dominant role of food prices in driving overall price levels (Iddrisu & Alagidede, 2020; Ginn & Pourroy, 2020); their volatility and persistence that dent inflation forecasting accuracy (Ginn & Pourroy, 2020; Alper et al., 2016; Portillo et al., 2016) and the associated uncertainty in the conduct of monetary policy (Ginn & Pourroy, 2020) are well known in the theoretical and empirical literature. These characteristics are even more pronounced in emerging and developing economies in view of the dominance of food in the consumption baskets of these economies, thereby making optimal conduct of inflation targeting framework a major challenge (see Iddrisu & Alagidede, 2020). Unsurprisingly, many emerging inflation targeting economies have struggled to achieve publicly announced inflation targets over the years and this can affect the credibility of policymakers.
Whether monetary policy exacts stability in food prices, as espoused by the theoretical literature (Ginn & Pourroy, 2020; Pourroy et al., 2016; Catao & Chang, 2015), is an important empirical question that has received little attention in the literature. So far, studies on this subject have focused largely on monetary policy and overall inflation to the neglect of food price stability. Much as some attempts have been made recently in the literature (Iddrisu & Alagidede, 2021; Iddrisu & Alagidede, 2020; Bhattacharya & Jain, 2020; Hammoudeh et al., 2015), fundamental limitations still linger. What makes food prices a major concern for monetary policy authorities is its underlying variability that minimises the accuracy of inflation forecasts; breeds uncertainty in the conduct of monetary policy; destabilise planning and income of farmers/producers and derail economic welfare for the poor in particular. Surprisingly, existing studies, save Iddrisu & Alagidede (2021, 2020), have tended to use models that completely ignore this all-important characteristic of food prices. Although Iddrisu & Alagidede (2021, 2020) employed the quantile regression analysis that captures tail dynamics resulting from outliers in food prices, such an approach fails to address the frequency of food price changes and deviations from the trend that are even more ruinous to inflation forecasting accuracy and engenders uncertainties in the conduct of monetary policy.
Importantly, all the existing studies have been situated exclusively in time domain, ignoring the fact that economic agents have distinct objectives over distinct horizons and frequencies. This obvious mishap was highlighted by Aguiar-Conraria et al. (2008), who posit that the actions of different economic agents are informed by different objectives across distinct horizons which eventually underlie numerous economic processes. The resulting macroeconomic data that are observed are essentially a crystallisation of these distinct economic agents’ objectives and horizons. To examine monetary policy effect on food prices in an exclusive time domain is to obscure the underlying distinct objectives and horizons of economic agents. Indeed, Aguiar-Conraria et al. (2018) argued that monetary policy affects over distinct horizons and especially cyclical frequencies are crucial for policymakers, given the distinct impact on social welfare over these different frequencies.
This book overcomes these limitations in the literature by adopting an approach that situates the monetary policy–food inflation nexus in time and frequency domains. It employs the wavelet-based quantile regressions to capture deviations of food prices from their trend and the accompanying monetary policy effect in stabilising such variabilities across distinct frequencies over time. The application of the quantile regression then gives the added advantage of capturing monetary policy effect on food prices at high, medium and low episodes of food inflation. This further illuminates the well-acknowledged asymmetry in monetary policy behaviour as discussed by Iddrisu & Alagidede (2021, 2020).
The focus of this book is on emerging and developing economies that have large proportions of food in their consumption baskets and high levels of indigence in their economies. Pourroy et al. (2016) reckon that 50% of the budget of households in developing countries is allocated to food alone. Specifically, the focus on inflation targeting economies such as Chile, Mexico, Turkey, Brazil, Hungary, Russia, Colombia, South Africa, Indonesia and Ghana brings into sharp focus, the several dynamics of inflation targeting such as the central role played by volatile food prices that distorts forecasting accuracy of inflation and highlights the essential toolkits of inflation targeting for inclusion in the tool boxes of central banks. The uncertainties that come with such variabilities present enormous concerns for monetary policymakers in exacting optimal policy. As a result, central banks that target inflation place significant importance on food price developments.
The findings show that the effect of monetary policy on food prices for the selected countries is mixed. While monetary policy exerts a positive impact on food prices over different horizons and distinct quantiles in Brazil, Chile, Ghana, Hungary, Mexico, Russia, South Africa and Turkey, its effect on food prices in Colombia and Indonesia is inconclusive. The results in these two countries differ across scales and quantiles. In Colombia, monetary policy delivers stability on food prices only over the short horizon of two to four months. At longer horizons, the effect of monetary policy on food prices in Colombia is positive. For Indonesia, food price stability is exacted by monetary policy over the short to medium horizon. At the longer horizon, monetary policy restriction engenders destabilization in food prices.
