The WHO has recently announced the global obesity epidemic. An economic model is developed in which globalisation factors generate health externalities and contribute to global obesity growth. The unbalanced panel data set contains the information for 79 countries over the period 1986–2008. Fixed‐effects panel data estimation and quantile regression analysis were used to analyse the data. The fixed‐effects panel model results indicate that the impact of trade openness and the globalisation social index (GSI) on global obesity rates is positive and significant, which is consistent with prior expectations, while surprisingly the foreign direct investments (FDI) has no impact on global obesity. While these results are interesting, they are hiding the effect of globalisation processes across the conditional distribution of the obesity variable. The use of quantile regression uncovered that the impact of the FDI and the GSI on low and average quantiles (low and average obesity rates in our sample) is positive and significant, while high quantiles are not affected. Since low and average quantiles (low and average obesity rates) are representative of the less‐ and medium‐developed countries, this result implies that social globalisation and FDI adversely impact obesity in less‐to‐medium developed countries. Trade openness generally has no impact on changes in obesity rates across quantiles.

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The law of one price (LOP) is one of the most frequently tested economic laws. Although called a law, it has probably been violated more than any other economic law (on the basis of the results of numerous empirical studies). Furthermore, the LOP is often utilized as the building block in international agricultural trade models without previously checking the validity of that assumption for that particular commodity. This can sometimes lead to erroneous conclusions that can have serious consequences on policy‐making decisions. This article represents a critical review of recent works that discuss how some factors, such as transportation (transaction) costs, tariffs, nontariff barriers, pricing to market, exchange rate risk, and trade regionalization, can prevent market arbitrage to force closer convergence of international prices. The validity of some methods often used for testing the LOP, such as cointegration analysis, is critically reviewed as well.

This article examines the impact of catastrophic hurricane events on income distribution in hurricane states in the United States. Media claims have been made and the perception created that the most damaging impact of hurricanes is on the lowest income population in the affected states. If these claims are true, they may have serious implications for the insurance industry and government policy makers. We develop a panel data, fixed effects econometric model that includes hurricane-impacted states as cross-sections using annual data for a period of almost 100 years. The Gini coefficient is used as a measure of income inequality, and is a function of normalized hurricane economic damages, gross domestic product (GDP), a set of socioeconomic variables that serves as a control, time trend, and cross-sectional dummy variables. Findings indicate that for every 100 billion US dollars in hurricane economic damages there is an increase in income inequality by 5.4 % as measured by Gini coefficient. Political, sociodemographic, and economic variables are also significant. These include such variables as the political party controlling the U.S. Senate, the proportion of nonwhite population by state, and GDP. Time trend is a positive and significant variable, suggesting an increase in income inequality over time. There are significant differences among the states included in the study. Our results demonstrate that different segments of the population are differently impacted by hurricanes and suggest how that differential impact could be considered in future government policies and business decisions, particularly those made by the insurance industry.

Obesity is considered one of the largest public health problems in the United States today. The premise for our study is a body of results from medical research showing that sweetened foods, i.e., an increased consumption of sugars, leads first to sugar addiction and second to carbohydrate addiction and increased consumption of fats. The latter feature is actually responsible for the increase in body mass index (BMI), but the trigger that produces cravings for extra calories is sugar and sweeteners. Based on our results, a myopic model of addictive behavior in food consumption seems to capture the food consuming habits and related outbreak of obesity among the American population. Our results indicate that lower current and past real prices of sugar contribute significantly to higher values of BMI, and increase the likelihood of becoming obese in the United States. Copyright (c)2008 International Association of Agricultural Economists.

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