The objective of this article is to explain the characteristics of the agri-food exporting boom experienced by the Latin American countries between 1994 and 2019 and its determining factors. In so doing, we analyse the evolution of exports, their composition by product, the principal origins and destinations, the importance of regional trade agreements and the behaviour of export prices. Furthermore, a series of gravity models are estimated, using the agri-food exports of nineteen Latin American countries to their 186 main trading partners between 1994 and 2019. These models are estimated for total agri-food exports and for their breakdown into three product groups. Among the main determinants identified, our results suggest that external demand and the proliferation of regional trade agreements were the primary reasons for this export boom. Finally, we evaluate these results within the context of the region's economic history.

This study uses gravity models to explain bilateral patterns of global wine trade since 1962. This is, to our knowledge, the first study on global wine trade covering the second wave of globalization as a whole. The results suggest that the impact of distance, common language, and common colonizer post-1945 on wine trade was lower in the 1991–2019 period than in the 1962–1990 period. We also use gravity models to explain the impact on bilateral wine trade patterns of similarities across countries in the mix of winegrape varieties in their vineyards. Although our models do not allow us to identify causality, the results suggest that countries trade more wine with each other the closer their mix of winegrape varieties.

During the first wave of globalization, Argentina was among the most internationally integrated economies, experiencing a rising trend in trade openness and a tremendous increase in labor due to migration. In this paper, we empirically show the central role immigration had in boosting exports and imports in the years 1870–1913 by considering Argentine bilateral trade and migration from eight European countries (Austro-Hungarian Empire, Belgium, France, Germany, Italy, Spain, Switzerland, and United Kingdom). We use a migration-augmented gravity model to estimate the contribution of the massive inflows of Europeans, and we find that the main pro-trade effect was on imports: a percent 10% increase in migrants from a particular country would increase imports by up to 8% from that same country. We do not find the same effect on exports. The disproportionate decrease in transportation rather than communication costs may explain why the latter are relatively more decisive for exports than for imports. To overcome the problem of reverse causality and endogeneity, we use migration flows to the US from the eight European countries as an instrumental variable. In so doing, we aim at capturing the same push (but not Argentine pull) factors inducing European out-migration.

We developed a novel method to align two data sources (TB notifications and the Demographic Health Survey, DHS) captured at different geographic scales. We used this method to identify sociodemographic indicators – specifically population density – that were ecologically correlated with elevated TB notification rates across wards (~100 000 people) in Dhaka, Bangladesh. We found population density was the variable most closely correlated with ward-level TB notification rates (Spearman's rank correlation 0.45). Our approach can be useful, as publicly available data (e.g. DHS data) could help identify factors that are ecologically associated with disease burden when more granular data (e.g. ward-level TB notifications) are not available. Use of this approach might help in designing spatially targeted interventions for TB and other diseases in settings of weak existing data on disease burden at the subdistrict level.

We look at the effect of the WTO on stabilizing international trade using both a fixed-effects and an event study approach. Our results show that WTO members experience lower trade volatilties in a predictable and integrated system. In addition, we focus on the trade volatility comovement among countries in a multilateral framework. Previous research has mainly focused on WTO membership in a bilateral trade framework, which only allows interactions between two trade partners without considering any possible influence from other countries. A bilateral trade framework does not fully capture the effect of WTO membership, nor does it investigate why the multilateral platform of the WTO should exist. With a unique setup estimating interactions among multiple trading dyads, we find strong evidence supporting positive correlation or comovement of trade volatilities across trading pairs. Such a comovement appears much stronger among WTO members than between WTO and non-WTO members. Due to the feedback mechanism among dyads in a multilateral framework, such as the WTO, bilateral trade stability may further stabilize the global trade. Our results remain robust to a battery of sensitivity checks.

The WTO SPS Agreement sets a framework of rules that encourages harmonization through international standards. However, there is a lack of empirical research at the macro-level on how such international standards affect trade flows. This study conducts a general impact analysis on one of the most widely used food-related international standards in the world, the ISO22000, accounting for the different product types and country groups. The Codex Alimentarius Commission, one of three sister organizations of the SPS Agreement, notably participated in developing this standard that is based on its Food Code, harmonizing the Hazard Analysis and Critical Control Points (HACCP) and Good Manufacturing Practice (GMP). This study employs recent developments in using the gravity model, along with uniquely employed additional specifications to enhance further the reliability of the estimates. Results show that ISO22000 diffusion negatively affects the exports of processed products that are the major export goods of developed countries. Primary and semi-processed products that compose the majority of developing country exports are not significantly affected, providing evidence against the concerns for the compliance burdens of developing countries when being certified to the standard. The burdens may depend more on the degree of processing of the exported goods rather than on a country's development status.

While France leads the way in the Chinese import market of wine, China is France's third largest wine export market by value. In this article, I analyze the determinants of France's wine exports to China, differentiated by French wine growing regions. I estimate a simple demand using a dataset on wine shipments of 100 different types of French bottled wines to China between 1998 and 2015. I find a wide range of income and price effects across French regions—a range not unlike those found by studies spanning multiple countries. Bordeaux wines exhibit the largest Chinese income elasticity. However, other French regions appear to catch up. Price elasticity, meanwhile, is particularly low for highly reputable wines, but quite high for wines targeting middle-class customers and wines from regions traditionally known for white wines. (JEL Classifications: F10, F14, L66, Q17)

Since trade must cross borders, to what extent do border walls affect trade flows? We argue that border walls can reduce trade flows. Even if the objective is to only stem illicit flows, border walls heighten “border effects” that can also inhibit legal cross-border flows. Using a gravity model of trade that reflects recent developments in both economic theory and econometrics, we find that the creation of a wall is associated with a reduction in legal trade flows between neighboring countries. We provide a battery of evidence that suggests this reduction is not simply a function of worsening bilateral relations. Our findings have implications for understanding how governments have taken measures to assert sovereign control of their borders in an age of increasing economic globalization.

Assuming horizontal differentiation and using an expanded gravity model, the main objective of this article is to assess the determinants of Portuguese wine exports. Horizontal differentiation is considered, with still and fortified wines being distinguished, as well as three distinct designations of origin: Vinho Verde, Douro, and Port wines. The results from the period between 2006 and 2016 suggest that wineries and private and public agencies should focus their commercial and policy efforts on countries with high purchasing power and/or with great potential for growth, regardless of whether the customs costs are higher. Moreover, it is concluded that horizontal differentiation influences the export determinants, suggesting there should exist different internationalization strategies for distinct types of wine. (JEL Classifications: F10, F14, L66)

We introduce a new modelling framework to explain socio-economic differences in mortality in terms of an affluence index that combines information on individual wealth and income. The model is illustrated using data on older Danish males over the period 1985–2012 reported in the Statistics Denmark national register database. The model fits the historical mortality data well, captures their key features, generates smoothed death rates that allow us to work with a larger number of sub-groups than has previously been considered feasible, and has plausible projection properties.

Human movement contributes to the probability that pathogens will be introduced to new geographic locations. Here we investigate the impact of human movement on the spatial spread of Chikungunya virus (CHIKV) in Southern Thailand during a recent re-emergence. We hypothesised that human movement, population density, the presence of habitat conducive to vectors, rainfall and temperature affect the transmission of CHIKV and the spatiotemporal pattern of cases seen during the emergence. We fit metapopulation transmission models to CHIKV incidence data. The dates at which incidence in each of 151 districts in Southern Thailand exceeded specified thresholds were the target of model fits. We confronted multiple alternative models to determine which factors were most influential in the spatial spread. We considered multiple measures of spatial distance between districts and adjacency networks and also looked for evidence of long-distance translocation (LDT) events. The best fit model included driving-distance between districts, human movement, rubber plantation area and three LDT events. This work has important implications for predicting the spatial spread and targeting resources for control in future CHIKV emergences. Our modelling framework could also be adapted to other disease systems where population mobility may drive the spatial advance of outbreaks.

From December 2014 to June 2015, U.S. poultry was affected by highly pathogenic avian influenza that led to destruction of 48 million birds and losses in international trade. During the event, 45 countries placed trade restrictions on U.S. poultry exports, varying from regionalized to national poultry restrictions. Using a gravity model of trade, the effects on quantity traded is estimated for poultry exports at the aggregated and disaggregated commodity level to understand product flows during an event. Results indicate U.S. poultry exports benefit from countries willing to apply limited trade restrictions, and the trade impact varies across disaggregated commodities.

In dynamic networks, the presence of ties are subject both to endogenous network dependencies and spatial dependencies. Current statistical models for change over time are typically defined relative to some initial condition, thus skirting the issue of where the first network came from. Additionally, while these longitudinal network models may explain the dynamics of change in the network over time, they do not explain the change in those dynamics. We propose an extension to the longitudinal exponential random graph model that allows for simultaneous inference of the changes over time and the initial conditions, as well as relaxing assumptions of time-homogeneity. Estimation draws on recent Bayesian approaches for cross-sectional exponential random graph models and Bayesian hierarchical models. This is developed in the context of foreign direct investment relations in the global electricity industry in 1995–2003. International investment relations are known to be affected by factors related to: (i) the initial conditions determined by the geographical locations; (ii) time-dependent fluctuations in the global intensity of investment flows; and (iii) endogenous network dependencies. We rely on the well-known gravity model used in research on international trade to represent how spatial embedding and endogenous network dependencies jointly shape the dynamics of investment relations.

A gravity model was used to determine the impact of exchange rate volatility on turkey trade flows. Previous analyses of aggregate agricultural sectors or products have assumed the effect of exchange rate volatility is uniform, that is, it impacts the individual components of the aggregates in the same way. This is highly unlikely, given the differences in biological and marketing factors across commodities and sectors. In order to address this issue, we examined how exchange rate volatility affects international turkey trade rather than the more commonly analysed ‘poultry’ trade. Findings revealed that the effects of short- and long-run exchange rate volatility on bilateral turkey trade are positive and statistically significant. Increasing distance between importing and exporting countries has a negative effect on turkey trade flows, while being a member of NAFTA and EU-27 has positive impacts on those flows.