Climate Change and Food Price Inflation in African Economies: Does the Trade Partner Hurt?

Background Food bank use has been rising in the EU, raising concern about food hardship and associated health consequences. While attributed to economic downturn or rising costs of living, no studies have systematically examined food hardship in the EU or investigated explanatory factors. Here we examine within-country trends in food hardship over 2004 to 2012, and test the hypotheses that economic downturn and rising costs of living are associated with rising food hardship, but that effects are mitigated by social protection spending. Methods Data on GDP, unemployment, food price inflation, housing cost inflation, average wages, and social protection spending per capita were compiled for 21 EU countries with available data from Eurostat and OECD databases for 2004 to 2012. We constructed indices for costs of living relative to wages from data on food inflation and housing inflation relative to wage inflation. Fixed effect multiple regression models were used to examine how GDP, unemployment, wages and costs of living indices related to food hardship, as indicated by reported inability to afford meat or equivalent. Results After a steady decline in food hardship from 2004 to 2009, this trend reversed, with food hardship rising from an average prevalence of 7.72% (SD = 7.06) to 9.10% (SD = 7.86) from 2009 to 2012. There was marked variation however, where food hardship continued to decline in some countries over this period, but rose by over 5 percentage points in others. We observed that for every 1 percentage point rise in unemployment, there was a 0.45 percentage point increase in food hardship (95% CI: 0.039 to 0.86%), and for every $100 increase in average wages, food hardship declined by 0.34 percentage points (95% CI: –0.53 to –0.15%). Food price and housing cost inflation were not directly related to food hardship, but there was a significant interaction between food price inflation and wage inflation, which indicated that a combination of rising food prices and falling wages compounded to increase food hardship more than either factor alone. Social protection had significant modifying effects on associations of food hardship with unemployment and the index of food price inflation relative to wages. Where there was high social protection, associations were not detectable. Conclusion Food hardship has been rising across countries in the EU in association with unemployment, falling wages, and rising food prices relative to wages, but social protection spending mitigated these associations.

The dynamics, scale, and direction of mediating relationships between climate change shocks, Insecurity and food price inflation has recently caught the attention of researchers and has become a subject of intense debate. Yet, studies differ on the type, scale, and evidence of the relationship between climate change shock, insecurity, and food price inflation. Thus, this study empirically investigates the affiliation between insecurity, climate change shocks and food price inflation in Nigeria. To achieve this objective, we adopted both Linear and Nonlinear Autoregressive Distributed Lag approach of cointegration analysis, with time series data spanning 2011M1-2022M12. The results show very strong evidence of a cointegrating relationships between insecurity, climate change shock and food price inflation in Nigeria. Both the ARDL and NARDL bound tests show that the variables of interest have symmetric and asymmetric long run relationships. We found that insecurity and climate change shock are significant determinant of heightened food prices in Nigeria within the study period. The Dynamic Multiplier graph with its accompanying 95 percent confidence interval for statistical inferences indicate that explanatory variables exert significant influence on the food price inflation in Nigeria. This study, therefore, recommends policy interventions to support households adversely impacted by insecurity in the affected zones. Also, the Nigerian state is encouraged to transit from traditional agricultural system to Climate-Smart Agriculture to meet future needs and climate related challenges.

This paper focuses on precipitation anomaly as a proxy for climate change to investigate how climate change affects food price inflation in Nigeria. An ARDL model was employed to entangle and quantify drivers behind the relationship between precipitation anomaly and food price inflation. The result shows that a 1 per cent increase in precipitation anomaly implies an increase of 0.58 per cent in food inflation in the short run. At the same time, an increase of 1 per cent precipitation anomaly implies an increase of 0.11 per cent in food inflation in the long run. This means that precipitation anomaly pushes food prices upward, which affects inflationary trend in general and monetary policy effectiveness. To keep inflation under target, policy incentive towards adaptation and mitigation of climate change should be rolled out to tame climate-induced food price inflation in both long run and short run. Additionally, policy makers ought to gauge climate perception of economic agents in anchoring inflation expectation. This is in additional to monetary policy mechanism which ought to be sensitive to precipitation anomalies and other climate related shocks and risks as they affect the primary mandate of ensuring price stability.

The study delves into the critical issue of climate change and its detrimental impact on various regions worldwide, including Nigeria. It emphasizes the urgent need for global efforts to mitigate these effects and advocates for measures to address human activities contributing to climate dynamics. Specifically, the study empirically examines the affiliation between climate change shocks and food price inflation in Nigeria using a Nonlinear Autoregressive Distributed Lag (NARDL) approach. The dataset covers the period from January 2011 to December 2022.The empirical findings reveal a robust cointegrating relationship between climate change shocks and food price inflation in Nigeria. Notably, climate change shocks significantly contributed to rising food prices within the study period. Furthermore, the Error Correction Term (ECT), estimated at 52 percent, indicates that food price inflation adjusts by 52 percent in the current month to counteract the initial shock experienced in the previous month. The Dynamic Multiplier graph, along with a 95 percent confidence interval, demonstrates that the explanatory variables exert substantial influence on food price inflation in Nigeria during the study period. Considering these findings, the study recommends that Nigeria should transit from traditional agricultural practices to Climate-Smart Agriculture to address future needs and climate-related challenges. Additionally, the government and stakeholders should implement alternative practices such as irrigation and the replenishment of shrinking water bodies in the Sudan and Sahel savannah regions.

The inflation picture is more heterogeneous in transition and developing economies. In Ethiopia, the year-on-year food inflation has increased by 42.0 percent in September 2021 as compared to the one observed in September 2020. The main objective of this study is to investigate the dynamics of food price inflation and its determinants in Ethiopia. For data analysis autoregressive distributed lag (ARDL) to con-integration model was used. The results suggested that food price inflation appears to be strongly significant and positive in explaining current food inflationary pressures in the short-run and negative in the long run. In effect, a one percent rise in food prices in the previous year causes the actual food prices to increase in short-run and declines in the long-run. These results emphasized the importance of inflation inertia and persistent price-price spiral movement in Ethiopian food price dynamics. Money supply positively influenced food price inflation growth in the short-run and in long-run. In the same way, the exchange rate influenced food price inflation positively in the short-run and long-run. Food inflation is also negatively influenced by real gross domestic product in US Dollar in both the short-run and long-run. In the same way government budget deficit and general consumer price index affected food price inflation significantly. Therefore, as policy recommendation, policy makers need to take appropriate measure to follow tight monetary policy and find the right balance between money demand and economic growth when needed without over-pumping money into the economy which causes inflation. As it is inferred from the research work the influence of exchange rate on food price is for both the short-run and long-run so that the government needs to focus on the way to control instability in exchange rate by devising a right macroeconomic policy to constrain the upward spiral movement of food price inflation. In regarding budget deficit and general consumer price index, the right decision to stabilize the country’s economy by the government is required. Keywords: Food Price Inflation. Dynamics, ARDL, Con integration DOI: 10.7176/JESD/13-21-03 Publication date: November 30 th 2022

To examine whether changes in food prices are associated with changes in obesity prevalence among women in developing countries, and assess effect modification by individual socioeconomic status (SES). Longitudinal study of country-level food price inflation temporally and geographically linked to anthropometric data on non-pregnant adult women (n = 295,984) in 31 low-income and middle-income countries over the 2000-2014 time period, using separate multivariable multilevel growth models of five SES indicators. Post-estimation analysis computed the relationship between food price inflation and predicted mean probabilities of being obese, by SES. Rising food price inflation was strongly associated with women's obesity prevalence, and SES consistently modified the relationship. Regardless of indicator used, higher food price inflation was positively associated with obesity among women in top SES categories, but was flat or negative among women in low SES categories, averaging over time. The SES differences were widest across educational strata and were most pronounced when food price inflation was highest. Overall, for every 1-unit increase in food price inflation, predicted mean obesity prevalence was between 0.02 and 0.06 percentage points greater in women of high SES compared to low SES women. There is a strong link between food price inflation and obesity in adult women in developing countries which is clearly modified by individuals' SES. Greater food price inflation was associated with greater obesity prevalence only among women in higher SES groups, who may be net food buyers most at risk of obesity in low-income and middle-income countries.

High and volatile food prices pose a significant policy challenge around the world, and an understanding of the dynamics of food price inflation and volatility is essential in designing appropriate policy responses. Using the panel data for 72 countries from 2000 to 2011, the paper assesses the international transmission of food price inflation and volatilities as well as the effects of various internal and external factors on domestic food price inflation and volatility. The paper offers evidence in support of the international transmission of food price inflation and volatility. Specifically, the paper finds that the domestic food price inflation in Asia is strongly associated with the lagged value of global food price inflation (using the FAO food price index), while volatility spillovers from global to domestic food prices are rather contemporaneous. The paper also finds that both national food price inflation rates and volatilities are strongly associated with both intra- and extra- regional food price inflation rates and volatilities, respectively. The findings also suggest that higher economic growth rates, greater shares of food in merchandise imports, and smaller increases in the share of food in merchandise imports lead to lower domestic food price inflation. An appreciation of local currency, greater political stability, and higher income level are also found to lower domestic food price inflation. On the other hand, higher economic growth rates lead to lower volatilities of food prices.

PurposeThe purpose of this paper is to investigate the food price inflation convergence across countries and regions. This study aims to identify the key drivers for food price inflation across countries and regions.Design/methodology/approachWe test whether the international food price inflations are converging over time using the log t convergence test and clustering analysis. These inflation data are collected from the Food and Agriculture Organization of the United Nations.FindingsThe test results suggest that there is little evidence of overall convergence. Then we utilize a clustering algorithm and the results support that there is strong evidence of multiple convergence clubs. In addition, we examine the transition path of the various convergence and find that social stability regulation together with economic conditions are important determinants of convergence club membership.Research limitations/implicationsFirst off, local conflict and economic environment result in food supply and prices, but this study is limited to the dynamics of prices.Practical implicationsFood prices inflations are not converging to single common price inflation, but there exist subgroups of countries or regions within which food price inflation tends to converge. These groupings tend to be related to the economic development and social stability of countries and regions.Social implicationsThe authors believe that any analysis of food price inflations that does not consider the political environment and economic conditions dynamics will likely be omitting important components of food price dynamics.Originality/valueThis study uses a unique data set covering 198 countries and regions and provides a comprehensive analysis of international food price inflation convergence identifying the key drivers of convergence club membership.

This study examines the dynamic linkages between food price inflation and its volatility in the context of Sri Lanka. The empirical evidence derived from the monthly data for the period from 2003M1 to 2017M12 for Sri Lanka. The relationship between inflation rate and inflation volatility has attracted more attention by theoretical and empirical macroeconomists. Empirical studies on the relationship between food inflation and food inflation variability is scarce in the literature. Food price inflation is defined as log difference of food price series. The volatility of a food price inflation is measured by conditional variance generated by the FIGARCH model. Preliminary analysis showed that food inflation is stationary series. Granger causality test reveals that food inflation seems to exert positive impact on inflation variability. We find no evidence for inflation uncertainty affecting food inflation rates. Hence, the findings of the study supports the Friedman-Ball hypothesis in both cases of consumer food price inflation and wholesale food price inflation. This implies that past information on food inflation can help improve the one-step-ahead prediction of food inflation variability but not vice versa. Our results have some important policy implications for the design of monetary policy, food policy thereby promoting macroeconomic stability.

The issue of volatile food prices is a consistent problem for American consumers, as rising prices make it challenging to afford nutritious food that meets dietary standards. Various complex factors influence this price volatility, including economic conditions, weather patterns, global trade, energy prices, and more. Notably, the impact of food price increases is not equal for everyone. Low-income individuals and those in rural areas are disproportionately affected. A comprehensive understanding of the driving factors is essential to tackle this issue effectively. We employ advanced time-series techniques such as Vector Error Correction Models (VECM) and modern causal inference methods such as probabilistic graphical models implemented via machine learning and artificial intelligence approaches on monthly data from 2000 to 2021 to investigate the U.S. food price inflation issue. These methods help unravel the intricate dynamics among key variables driving food price inflation. The study aims to achieve several objectives. It intends to (1) clarify how factors influencing food price inflation in the U.S. change over time using VECM models, (2) establish causal relationships among interconnected variables to develop probabilistic graphical models using innovative search algorithms, and (3) create and validate forecasts related to U.S. food price inflation. The end goal is to provide actionable insights for policy design. Results show that food price inflation is heavily tied to commodity pricing and pricing for medical services. Additionally, historical decompositions for COVID-19 show ties between food price inflation and energy inflation.

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.

The relationship between inflation rate and inflation volatility has attracted more attention by theoretical and empirical macroeconomists. Empirical studies on the relationship between food inflation and food inflation variability is scarce in the literature. This study examines the intertemporal dynamic linkages between food price inflation and its volatility in the context of Sri Lanka. The empirical evidence derived from the monthly data for the period from 2003M1 to 2017M12 for Sri Lanka. Food price inflation is defined as log difference of food price series. The volatility of a food price inflation is measured by conditional variance generated by the FIGARCH model. Granger causality tests show that food inflation seems to exert positive impact on inflation variability. Hence, the findings of the study supports the Friedman hypothesis in both cases of consumer food price inflation and wholesale food price inflation. This implies that past information on food inflation can help improve the one-step-ahead prediction of food inflation variability but not vice versa. Our results have some important policy implications for the design of monetary policy, thereby promoting macroeconomic stability.

BackgroundCurrently, food price inflation is a widespread issue in Bangladesh as well as the rest of the world. Malnutrition is a common issue among children that can have long-lasting effects on their development and overall health. There have been lots of studies conducted to identify the factors responsible for child malnutrition, but inflation is rarely considered a factor in child malnutrition. We aimed to determine the relationship between food price inflation and stunting (Height-for-Age Z-score (HAZ)) in children under five years of age in Bangladesh.MethodThe study utilized food price data from the World Food Programme database and malnutrition (stunting) information from the 2014 and 2017-18 Bangladesh Demographic Health Surveys (BDHS). This includes the total study period from 2009 to 2018. Food prices were linked to the BDHS dataset using each child’s birth month. For each child, the average food prices from 9 months prior to 5 months post-birth, including their birth month, were recorded to calculate month-to-month inflation. This inflation was computed for rice (coarse), oil, wheat flour, and lentils by comparing the price sum of each item from one month to the previous month and dividing by the total price of the preceding month. A generalized linear regression model was used to assess the relationship between food price inflation and stunting, with stunting as the dependent variable. Other explanatory variables included wealth index, sex of the child, height, weight, mother’s education, respondent’s current pregnancy, and breastfeeding status.ResultsOur study has revealed that food price inflation has a significant negative effect on stunting, with a coefficient of -0.127 (p < 0.001). Furthermore, we have identified several other factors that have also significantly negative associations with stunting, including the wealth index (p < 0.001), mother’s education level (p < 0.001), mother’s pregnancy status (p < 0.001), breastfeeding (p < 0.001), child’s age (p < 0.001). child’s weight (p < 0.001) has significantly positive effect on stunting. However, we did not find any significant differences in stunting between boys and girls.ConclusionIn conclusion, the findings of this study underscore the significant negative impact of food price inflation on child stunting, emphasizing the need to acknowledge this factor alongside others. These results highlight the critical role of addressing food price inflation as a key determinant of stunting, in conjunction with various other contributing factors, in efforts to combat childhood malnutrition.

The objective of this study is to empirically investigate: i) the extent in which shipping costs can cause and predict the food inflation in trinidad and tobago (t&amp;t); ii) the extent in which international food prices can drive food inflation in T&amp;T; and iii) the impact of the Russia-Ukraine conflict on food prices in t&amp;t. As a fourth sub-objective, this study seeks to provide policy recommendations to address the food price inflation in t&amp;t. A structural model is sought as it can use information about the past prices of the international food prices and shipping rates to forecast t&amp;t's food price inflation. this study used monthly data on t&amp;t retail price index food subcategory, the FAO Food Price Index (FFPI), and the Freightos Baltic Index over the January 2015 to November 2022 period. the Support Vector Regression (SVR) model was applied and used the FFPI and Freightos Baltic Index as the leading indicators to forecast t&amp;t's food price inflation. this study found that the FAO Food Prices does and the Freightos Baltic Index does have an impact on food prices in t&amp;t. Secondly, based on the FAO index and the Freightos Baltic Index, t&amp;t's food price inflation should be 14.91% lower than its present value. third, in a Markov Switching regression, the war dummy was only significant in the second regime, statistically suggesting that the Russia-Ukraine conflict only had a short term effect on t&amp;t's food prices. this contributed to the literature as it introduced a new test to investigate predictive causality. Policy measures to increase the agriculture output and address the food price inflation in t&amp;t include adopting sustainable farming practices such as integrated pest management and the sustainable water management, and encouraging aquaponics. Received: 24 February 2023 | Revised: 13 March 2023 | Accepted: 14 March 2023 Conflicts of Interest The author declares that he has no conflicts of interest to this work.

Status of agriculture and food security in post-COVID-19 Africa: Impacts and lessons learned