Cong S. Pham

Bio: Cong S. Pham is an academic researcher from Deakin University. The author has contributed to research in topics: Medicine & Gravity model of trade. The author has an hindex of 9, co-authored 29 publications receiving 1140 citations.

Trading on Time

Abstract: The authors determine how time delays affect international trade using newly collected World Bank data on the days it takes to move standard cargo from the factory gate to the ship in 126 countries. They estimate a modified gravity equation, controlling for endogeneity and remoteness. On average, each additional day that a product is delayed prior to being shipped reduces trade by at least 1 percent. Put differently, each day is equivalent to a country distancing itself from its trade partners by 70 kilometers on average. Delays have an even greater impact on developing country exports and exports of time-sensitive goods, such as perishable agricultural products. In particular, a day's delay reduces a country's relative exports of time-sensitive to time-insensitive agricultural goods by 6 percent.

Trading on Time

Abstract: We determine how time delays affect international trade, using newly-collected World Bank data on the days it takes to move standard cargo from the factory gate to the ship in 126 countries. We estimate a modified gravity equation, controlling for endogeneity and remoteness. On average, each additional day that a product is delayed prior to being shipped reduces trade by at least 1 percent. Put differently, each day is equivalent to a country distancing itself from its trade partners by 70 km on average. Delays have an even greater impact on developing country exports and exports of time-sensitive goods, such as perishable agricultural products. In particular, a day's delay reduces a country's relative exports of time-sensitive to time-insensitive agricultural goods by 6 percent.

Estimating the gravity model when zero trade flows are frequent

Abstract: In this paper we estimate the gravity model allowing for the pervasive issues of heteroscedasticity and zero bilateral trade flows identified in an influential recent paper by Santos Silva and Tenreyro. We use Monte Carlo simulations with data generated using a heteroscedastic, limited-dependent-variable process to investigate the extent to which different estimators can deal with the resulting parameter biases. While the Poisson Pseudo-Maximum Likelihood estimator recommended by Santos Silva and Tenreyro solves the heteroscedasticity-bias problem when this is the only problem, it appears to yield severely biased estimates when zero trade values are frequent. Standard threshold-Tobit estimators perform better as long as the heteroscedasticity problem is satisfactorily dealt with. The Heckman Maximum Likelihood estimators appear to perform well if true identifying restrictions are available.

Estimating the gravity model when zero trade flows are frequent and economically determined

Abstract: This paper evaluates the performance of alternative estimators of the gravity equation when zero trade flows result from economically-based data-generating processes with heteroscedastic residuals and potentially-omitted variables. In a standard Monte Carlo analysis, the paper finds that this combination can create seriously biased estimates in gravity models with frequencies of zero frequently observed in real-world data, and that Poisson Pseudo-Maximum-Likelihood models can be important in solving this problem. Standard threshold–Tobit estimators perform well in a Tobit-based data-generating process only if the analysis deals with the heteroscedasticity problem. When the data are generated by a Heckman sample selection model, the Zero-Inflated Poisson model appears to have the lowest bias. When the data are generated by a Helpman, Melitz, and Rubinstein-type model with heterogeneous firms, a Zero-Inflated Poisson estimator including firm numbers appears to provide the best results. Testing on real-world data for total trade throws up additional puzzles with truncated Poisson Pseudo-Maximum-Likelihood and Poisson Pseudo-Maximum-Likelihood estimators being very similar, and Zero-Inflated Poisson and truncated Poisson Pseudo-Maximum-Likelihood identical. Repeating the Monte Carlo analysis taking into account the high frequency of very small predicted trade flows in real-world data reconciles these findings and leads to specific recommendations for estimators.

Gravity Equations: Workhorse,Toolkit, and Cookbook

Abstract: This chapter focuses on the estimation and interpretation of gravity equations for bilateral trade. This necessarily involves a careful consideration of the theoretical underpinnings since it has become clear that naive approaches to estimation lead to biased and frequently misinterpreted results. There are now several theory-consistent estimation methods and we argue against sole reliance on any one method and instead advocate a toolkit approach. One estimator may be preferred for certain types of data or research questions but more often the methods should be used in concert to establish robustness. In recent years, estimation has become just a first step before a deeper analysis of the implications of the results, notably in terms of welfare. We try to facilitate diffusion of best-practice methods by illustrating their application in a step-by-step cookbook mode of exposition.

Credit Constraints, Heterogeneous Firms and International Trade

Abstract: This paper examines the detrimental consequences of financial market imperfections for international trade. I develop a heterogeneous-firm model with countries at different levels of financial development and sectors of varying financial vulnerability. Applying this model to aggregate trade data, I study the mechanisms through which credit constraints operate. First, financial development increases countries' exports above and beyond its impact on overall production. Firm selection into exporting accounts for a third of the trade-specific effect, while two thirds are due to reductions in firm-level exports. Second, financially advanced economies export a wider range of products and their exports experience less product turnover. Finally, while all countries service large destinations, exporters with superior financial institutions have more trading partners and also enter smaller markets. All of these effects are magnified in financially vulnerable sectors. These results have important policy implications for less developed economies that rely on exports for economic growth but suffer from poor financial contractibility.

Credit Constraints, Heterogeneous Firms, and International Trade

Abstract: Financial market imperfections severely restrict international trade ‡ows because exporters require external capital This paper identi…es and quanti…es the three mechanisms through which credit constraints aect trade: the selection of hetero- geneous …rms into domestic production, the selection of domestic manufacturers into exporting, and the level of …rm exports I incorporate …nancial frictions into a heterogeneous-…rm model and apply it to aggregate trade data for a large panel of countries I establish causality by exploiting the variation in …nancial development across countries and the variation in …nancial vulnerability across sectors About 20%-25% of the impact of credit constraints on trade is driven by reductions in total output Of the additional, trade-speci…c eect, one third re‡ects limited …rm entry into exporting, while two thirds are due to contractions in exporters'sales Finan- cially developed economies export more in …nancially vulnerable sectors because they enter more markets, ship more products to each destination, and sell more of each product These results have important policy implications for less developed nations that rely on exports for economic growth but suer from weak …nancial institutions

Racial and Ethnic Disparities in COVID-19-Related Infections, Hospitalizations, and Deaths : A Systematic Review.

Abstract: BACKGROUND: Data suggest that the effects of coronavirus disease 2019 (COVID-19) differ among U.S. racial/ethnic groups. PURPOSE: To evaluate racial/ethnic disparities in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection rates and COVID-19 outcomes, factors contributing to disparities, and interventions to reduce them. (PROSPERO: CRD42020187078). DATA SOURCES: English-language articles in MEDLINE, PsycINFO, CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Scopus, searched from inception through 31 August 2020. Gray literature sources were searched through 2 November 2020. STUDY SELECTION: Observational studies examining SARS-CoV-2 infections, hospitalizations, or deaths by race/ethnicity in U.S. settings. DATA EXTRACTION: Single-reviewer abstraction confirmed by a second reviewer; independent dual-reviewer assessment of quality and strength of evidence. DATA SYNTHESIS: 37 mostly fair-quality cohort and cross-sectional studies, 15 mostly good-quality ecological studies, and data from the Centers for Disease Control and Prevention and APM Research Lab were included. African American/Black and Hispanic populations experience disproportionately higher rates of SARS-CoV-2 infection, hospitalization, and COVID-19-related mortality compared with non-Hispanic White populations, but not higher case-fatality rates (mostly reported as in-hospital mortality) (moderate- to high-strength evidence). Asian populations experience similar outcomes to non-Hispanic White populations (low-strength evidence). Outcomes for other racial/ethnic groups have been insufficiently studied. Health care access and exposure factors may underlie the observed disparities more than susceptibility due to comorbid conditions (low-strength evidence). LIMITATIONS: Selection bias, missing race/ethnicity data, and incomplete outcome assessments in cohort and cross-sectional studies must be considered. In addition, adjustment for key demographic covariates was lacking in ecological studies. CONCLUSION: African American/Black and Hispanic populations experience disproportionately higher rates of SARS-CoV-2 infection and COVID-19-related mortality but similar rates of case fatality. Differences in health care access and exposure risk may be driving higher infection and mortality rates. PRIMARY FUNDING SOURCE: Department of Veterans Affairs, Veterans Health Administration, Health Services Research & Development.