Light fuel demand and public policies in Brazil, 2003–2013

The main objective of this article is to evaluate determinants of demand for light fuels in Brazil between 2003 and 2013. Through a vector autoregression analysis, an effort was made to identify and quantify the impact of different economic variables and public policy measures adopted during this period on the surprising increase in energy consumption by Brazil’s light-vehicle fleet. The results suggest that demand for energy by the light-vehicle fleet was influenced by an increase in income, by a decrease in fuel prices associated with a policy designed to prevent increases in the price of gasoline from pushing the inflation rate up, by a higher availability of credit for buying vehicles, and by a drop in the real price of those goods, with emphasis on countercyclical measures to waive the tax on industrialized products levied on new vehicles during economic downturns in the automotive industry.     

Stock price synchronicity to oil shocks across quantiles: Evidence from Chinese oil firms

This paper investigates behaviour of stock price synchronicity to oil shocks across quantiles for Chinese oil firms. The spillover effects of the oil market on a firm are segregated into firm-specific and market-wide information. First, our results report a higher level of synchronicity by dynamic conditional correlations than by R-square since the former better captures dynamic linear dependence. Second, we find strong evidence of size effect. In particular, stock price synchronicity is generally higher in large-cap firms than in small-cap ones. Oil shocks affect synchronicity in the upper quantiles differently based on firm size. Third, we also find that synchronicity responds to oil shocks significantly in extreme low quantiles, implying that shocks in the oil market are transmitted to Chinese oil firms via firm-specific information. Finally, we determine that oil shocks have little or no immediate impact on stock price synchronicity; instead, cumulative lagged effect is evident. This evidence highlights the lagging effect of spillover of oil shocks on Chinese oil firms.     

Is insurance normal or inferior? -A regret theoretical approach-

This study considers how changes in wealth affect insurance demand when individuals suffer disutility from regret. Anticipated regret stems from a comparison between the ex-post maximum and actual wealth. We consider a situation wherein individuals maximize their expected utility incorporating anticipated regret. The wealth effect on insurance demand can be classified into the risk and the regret effects. These effects are determined by the properties of the utility function and the regret function. We show that insurance can be normal when individuals place weight on anticipated regret, even though the utility function exhibit decreasing absolute risk aversion. This result indicates that regret theory is a possible explanation to the wealth effect puzzle, in which insurance is normal from empirical observation, but it should be inferior by theoretical prediction under expected utility theory.     

The effects of oil price shocks on inflation in the G7 countries

This study examines the effects of three types of oil price shocks on inflation in the G7 countries with a new method of isolating oil price shocks. Based on monthly data from January 1997 to January 2019, we find that each oil price shock has the largest effect on U.S. inflation among the G7 countries and each country’s response to oil price shocks is different. Moreover, a rolling-window analysis shows that supply shocks, demand shocks and risk shocks have dynamic effects on inflation. The effect of supply shocks on inflation is strong before the financial crisis, but weakens during the crisis. However, the effect of demand shocks increases sharply in this time. The effect of risk shocks mainly occurs during the financial crisis and the European debt crisis. In addition, this study uses two ways to verify the robustness of the results. Our empirical results have important implications for policymakers and manufacturers, since the results provide a good explanation for the response of inflation in the G7 countries to the oil price shocks from different sources.     

An econometric analysis of demand for food quantity and quality in urban China

This article offers an analytical framework for studying consumer demand for food quality based on a theory‐consistent demand model, namely, the Exact Affine Stone Index specification. Importantly, it accounts for unobserved consumer and regional heterogeneity, and allows for arbitrary Engel curves. The empirical value of our framework is illustrated in an econometric analysis of demand for food quality in China. Evaluating possible structural changes in consumer food expenditures in China is of paramount importance, given the ever‐increasing global role of China and the implications of the structural food preference changes for the global food system. The major findings emerging from this study indicate that income is an important determinant of demand for food quality and quantity with the relatively more affluent provinces having a higher affinity for food quality.     

Income and Price Elasticities of Demand in South Africa: An Application of the Linear Expenditure System

This paper investigates the expenditure patterns of South African households using detailed cross‐sectional expenditure and price data that varies across region and time. Linear expenditure system parameter estimates are used to calculate income and price elasticities for a number of product categories at different points of the income distribution. We find substantial variation in the price and income elasticities of demand for items across the income distribution, with the bottom quartile being extremely sensitive to increases in the price of food and clothing items, and the top quartile being as sensitive as households in developed countries.     

The impact of the COVID-19 pandemic on business expectations

We document and evaluate how businesses are reacting to the COVID-19 crisis through August 2020. First, on net, firms see the shock (thus far) largely as a demand rather than supply shock. A greater share of firms report significant or severe disruptions to sales activity than to supply chains. We compare these measures of disruption to their expected changes in selling prices and find that, even for firms that report supply chain disruptions, they expect to lower near-term selling prices on average. We also show that firms are engaging in wage cuts and expect to trim wages further before the end of 2020. These cuts stem from firms that have been disproportionally negatively impacted by the pandemic. Second, firms (like professional forecasters) have responded to the COVID-19 pandemic by lowering their one-year-ahead inflation expectations. These responses stand in stark contrast to that of household inflation expectations (as measured by the University of Michigan or the New York Fed). Indeed, firms’ one-year-ahead inflation expectations fell precipitously (to a series low) following the onset of the pandemic, while household measures of inflation expectations jumped markedly. Third, despite the dramatic decline in firms’ near-term inflation expectations, their longer-run inflation expectations have remained relatively stable.     

Time-frequency co-movements between oil prices and interest rates: Evidence from a wavelet-based approach

This paper investigates time–frequency co-movements between crude oil prices and interest rates. To test this relationship, the study applied a continuous wavelet and cross wavelet approaches to data from West Texas Intermediate (WTI) crude oil prices and interest rates in the United States (U.S.). Results from the sample period revealed significant relationships, in the intermediate term, between WTI crude oil prices and U.S. interest rates. Moreover, co-movements between oil price and interest rate variables were especially sensitive during abnormal political events and periods of financial ‘meltdown’. We further use Partial Wavelet Coherence (PWC) and Multiple Wavelet Coherence (MWC) methods to investigate the impacts of five major control variables namely GDP growth, unemployment, three-month Treasury bill, CPI index and industrial production index. The results show a powerful impact of control variables on oil-interest rates co-movements under different frequencies. Finally, we show evidence of co-integrating long run relationship between oil markets and control variables. These results have important implications for energy investors and policy makers.     

Quantifying and understanding land cover changes by large and small oil palm expansion regimes in the Peruvian Amazon

With rapid increases in global food demand and production, oil palm expansion constitutes a major emerging challenge for forest conservation in Amazonia and other tropical forest regions. This threat is evident in the Peruvian Amazon, where local and national incentives for oil palm cultivation along with growing large-scale investments translate into accelerated oil palm expansion. Environmental sustainability of oil palm cultivation in the Peruvian Amazon is contingent on policy incentives for expansion onto already-cleared lands instead of biodiverse, high carbon primary rainforests. Previous research indicates that while industrial plantations use less land area than local smallholders, companies have a higher tendency to expand into primary rainforests. However, the motivations behind these differing expansion scenarios remain unclear. In this study we combine data from optical and radar satellite sensors with training information, field discussions, and review of public documents to examine the policy incentives and spatial patterns associated with oil palm expansion by smallholders and industries in one of Peru’s most rapidly changing Amazonian landscapes: the Ucayali region of the city of Pucallpa. Based on our satellite-based land cover change analysis, we found that between 2010 and 2016, smallholders utilized 21,070 ha more land area for oil palm than industries but industrial expansion occurred predominantly in old growth forests (70%) in contrast to degraded lands for smallholders (56%). Our analysis of national policies related to oil palm expansion reveal policy loopholes associated with Peru’s “best land use” classification system that allow for standing forests to undergo large-scale agricultural development with little government oversight. We conclude that both sectors will need careful, real-time monitoring and government engagement to reduce old-growth forest loss and develop successful strategies for mitigating future environmental impacts of oil palm expansion.     

Long-term forecasting of fuel demand at theater entry points

Managing the distribution of fuel in theater requires Army fuel planners to forecast demand at the strategic level to ensure that fuel will be in the right place, at the right time, and in the amounts needed. This work presents a simulation approach to forecasting that accounts for the structure of the supply chain network when aggregating the demand of war fighters across the theater over the forecasting horizon. The resulting empirical distribution of demand at the theater entry point enables planners to identify forecast characteristics that impact their planning process, including the amplitudes and temporal positions of peaks in demand, and the estimated lead time to the point of use. Experimentation indicates that the forecasts are sensitive to the pattern of war fighter demand, the precise structure of the in-theater supply chain network, and the constraints and uncertainty present in the network, all of which are critical planning considerations.