Poisson Pseudo Maximum Likelihood Research Articles

Assessing the effects of hard and soft infrastructure on traditional vs supply-chain trade: the case of Central and Eastern EU member states (CEMS)

ABSTRACT The aim of this paper is to assess the role of hard and soft infrastructure in trade, distinguishing between traditional trade and supply-chain trade. Using factor analysis, we construct four aggregate trade facilitation indicators where we measure hard infrastructure as physical and ICT infrastructure, while soft infrastructure accounts for border efficiency and institutional efficiency. For traditional trade, we use bilateral trade data from UN Comtrade. Supply-chain trade is measured in terms of domestic value-added (DVAFX) embodied in foreign gross exports and foreign value-added (FVA) embodied in domestic gross exports obtained from Eora MRIO database. We use panel data regression analysis with an empirical model specification based on a gravity model and covering the 2000–2019 period. We estimate model with the Poisson Pseudo-Maximum Likelihood Estimator (PPML). To control multilateral trade-resistance terms (MRT), we included reporter and partner fixed effects along with country pair fixed effects. The results confirm a statistically significant relationship between hard and soft infrastructure and trade. ICT and border efficiency have the strongest impact on both types of trade. Supply-chain trade responds most intensely to improvements in institutional efficiency. Results imply that ICT infrastructure and border efficiency might hold even greater importance for CEMS’s traditional and supply-chain trade.

Export Competence of Cultural Goods: A Structural Gravity Analysis of the BRICS Trade

The BRICS economies contribute a substantial portion of global trade. However, the share of cultural export in their total exports has been declining over the past two decades. In this context, the current study examines cultural exports of BRICS compared to their aggregate exports using structural gravity model. For empirical estimation, we apply Poisson Pseudo-Maximum Likelihood High Dimensional Fixed Effects (PPMLHDFE) estimator for annual bilateral exports data. The results show that, as compared to non-cultural aggregate exports, exports of creative industries are more sensitive to geographical distance between countries. Nevertheless, positive effect of the similarity between trading partners in terms of language commonality, colonial relationship and shared border is more pronounced in case of cultural exports. Furthermore, we find that while the regional trade agreements promote exports in general, they remain inconsequential in case of cultural exports of BRICS. Additionally, the study uses cultural exports as a proxy for cultural proximity and finds that bilateral cultural exports facilitate the exports of non-cultural exports.

How much to invest for house purchase? The consumer purchase intention perspective of real estate investment decision

PurposeThis study is based on the consumer purchase intention (CPI) in real estate. The purpose of this study is to investigate the link between CPI and preferred individual investment capacity in buying real estate properties. This study investigates if commonly known factors of CPI such as attitude, social power or subjective norms, perceived behavior power or control, location, surrounding environment and socialization can influence a consumer’s preferred investment amount when buying a house, either for own use or for rental purpose.Design/methodology/approachA total of 334 respondents participated in this study. The survey data was analyzed using factor analysis technique, ordinary least square technique and Poisson pseudo maximum likelihood technique.FindingsThis study finds that location, surrounding environment, property/construction papers, roads, mosque/temple and fire services significantly influence the preferred investment amount of a real estate investor.Originality/valueThis study suggests that a link exists between CPI and real estate investment decision through factors such as location, surrounding environment, legal documentation and communication facility. These identified CPI factors require serious consideration by the real estate developers and their financing partners.

Understanding the global patterns of Venezuelan migration: determinants of an expanding diaspora

ABSTRACT The economic, political and humanitarian crisis in Venezuela intensified since 2015 and has led to the largest migration crisis in the region’s modern history. In parallel, the composition of the major destination countries has changed fundamentally. This paper investigates the factors determining the choice of destination country of Venezuelan migrants in the pre- and post-2015 period. Exploiting the United Nations migration dataset (for 230 countries from 1990 to 2017), we apply a Poisson Pseudo-Maximum Likelihood (PPML) estimator to a modified gravity model of migration. The results suggest that Venezuelans were generally choosing a certain destination country based on economic criteria in times of relative stability (1990 to 2015). However, this determinant loses its importance during times of crisis (2015 to 2017), when Venezuelans were primarily immigrating to geographically proximate nations. Consistently for both periods Venezuelans appear to migrate in larger numbers to destinations with an already established network of compatriots.

Evaluation of the Impact of Regional Trade Agreements on Indian Exports

This article scrutinises the repercussion of the regional trade agreements on Indian exports. The gravity model has been used for the analysis of two decades of panel data from 30 countries, spanning from 2001 to 2019. The gravity equation is estimated by the Ordinary Least Square (OLS) and Poisson pseudo-maximum likelihood (PPML) techniques using panel data regression. The PPML approach addresses the heteroskedasticity bias that is typically present in the OLS method. The study has revealed that the PPML results are more encouraging than those obtained based on the traditional OLS approach. According to the empirical findings, India’s trading partners in South Asia benefit more from its economic integration than India does. However, the measurement of country-specific degrees of globalisation has a negligible effect on fostering trade across select nations. JEL Codes: C1, F1, F2, F6

Does agricultural official development assistance facilitate foreign direct investment in agriculture: Evidence from 63 developing countries

AbstractAlthough past studies have separately explored the direct impact of agriculture official development assistance (ODA) and foreign development investment (FDI) on agricultural production, the nexus between these two elements is often neglected. This article aims to understand the linkage between agricultural ODA and FDI, using data from 63 developing countries from 1991 to 2019. Poisson pseudo maximum likelihood estimations reveal that agricultural ODA considerably promotes FDI in the agriculture, fishery and forestry sectors (FDI_aff) by approximately 0.5%, while its impact on FDI in the food, beverages and tobacco industries (FDI_fbt) is overall insignificant. Geographical and ecological conditions play a decisive role in accounting for FDI in agriculture. While coastal and land‐rich countries receive a significantly higher amount of FDI_aff and FDI_fbt, tropical countries are evidently more attractive destinations for FDI_fbt. The empirical analysis also shows that a peaceful social environment encourages FDI_aff. Well‐established legal systems and reductions in corruption facilitate FDI_aff, whereas the impact of overall institutional quality on agricultural FDI is insignificant. Results suggest that donors prioritise agricultural initiatives with higher positive spillover effects, such as programmes supporting food crop production and agricultural research.

The nonlinear effects of air pollution on criminal behavior: evidence from Mexico City and New York

This article proposes an inverted U-shape relationship between air pollution and criminal behavior. Exposure increases criminality by raising criminals’ taste for risk and violent behavior while also reducing it by changing the number of felons and crime opportunities in the market through exacerbated morbidity and avoidance behavior. I illustrate both mechanisms with an expected utility model of the decision to delict and a simplified search and matching frictions model between criminals and crime opportunities. Linear, quadratic, and nonparametric Poisson pseudo-maximum likelihood estimator panel models confirm this bell-shaped relationship for Mexico City and New York, suggesting that the linear association between pollution and criminality uncovered by late studies may be better estimated with nonlinear models.

Determinants of commuting flows in Germany

The paper studies commuting flows between German regions. Using panel data of 400 German regions from 2013 to 2019 we evaluate the effect of the wide range of indicators determining the magnitude of the commuting flows: demographic factors, indicators of the labour and real estate markets, welfare variables, social and educational system characteristics, etc. We employ the gravity model analysis with Poisson Pseudo Maximum Likelihood, allowing us to consider even the absence of commuters between regions. The novelty of the research is that the full structure of commuting flows, including the direction, is analyzed at the aggregated district level. In addition to other papers devoted to the economics of the labor market and focused mostly on individual data and selected determinants, we investigate a wide range of possible factors and conclude that the main macroeconomic factors determining both the intensity and direction of commuting flows: population, unemployment rate, cost of leasing housing and the number of companies per 10000 people. We also find that commuting flows between regions in the same land are 202% higher than between regions from different lands, and commuting flows between neighbouring regions are 414.5% higher than between regions without a common border.

Defending the nation, securing the economy

Literature on the effects of military expenses and GDP is mixed, although a significant body of research supports the hypothesis that military expenses positively impact GDP. To contribute to the literature, this article analyses whether military expenditures influenced GDP in 27 European Union member countries from 1998 to 2021 by studying two clusters specific to the analysed countries: NATO and non-NATO countries. The way in which military expenditures affect GDP has been analysed using both the classic static models for panel data (pooled OLS, fixed effects, random effects, feasible generalized least squares, panel corrected standard errors, Poisson pseudomaximum likelihood regression) as well as by applying dynamic panel model system GMM, reverse causality, and half-panel jackknife regression models, with unemployment and inflation selected as control variables. The findings indicate that the current values of military expenditures positively influence GDP in both clusters, while past values of military expenditures positively influence GDP in the NATO EU countries and negatively affect GDP in the non-NATO EU countries. There are several key differences between NATO EU members and non-NATO EU members, particularly in regard to their security commitments and defence spending. NATO members are part of a mutual defence pact, agreeing to the principle of collective defence, which also impacts public defence policies and public budgets. This paper offers practical value to policymakers, stakeholders, and academicians. In addition, it has two significant political implications. First, it highlights the role of military expenditures as a catalyst for economic growth but does not underestimate the dangers of using military spending as a pretext to stimulate employment. Second, it establishes the optimal proportion of military expenditures required to fulfil two essential targets of national and European policies – security and welfare.

Uloga bilateralnih investicionih sporazuma u podsticanju internacionalizacije preduzeća u Srbiji

Bilateral investment treaties are traditionally considered to be an instrument for attracting foreign direct investment in Serbia. However, their provisions may also support the internationalization of its enterprises. In this paper, we explore how effective bilateral investment treaties are in promoting the most challenging aspect of the internationalization of enterprises in Serbia -foreign direct investment outflows. Additionally, we investigate the role of other main motivations for the investment outflows. We conduct our analysis by estimating a gravity model using the panel data on Serbia and its 147 partner economies, observed in the period between 2011 and 2019. The gravity model was estimated using the Poisson pseudo-maximum likelihood estimator. We find that bilateral investment treaties have a statistically significant positive effect on bilateral foreign direct investment outflows. Furthermore, the outflows are particularly affected by the treaties containing higher anti-discrimination standards and providing a more liberal investment regime. Unilateral liberalization of the host countries' investment regime is also found to be positively associated with the investment outflows, whereas both the geographic and psychic distances have negative effects. Market-seeking motives of the internationalizing enterprises in Serbia are revealed to be the dominant driver of the investment. The results provide useful implications for the policymakers aiming to support the internationalizing efforts of the enterprises and the consequent improvement of the international competitiveness of Serbian economy.

Modeling of the Nexus Between Environmental Regulations of Trade Partners and Export Volumes: Analysis of Russian Regions

Export development is one of the priorities of the Russian economy. Exporters and companies planning to enter the international market face a number of limiting factors. Transitional climate risks, mainly represented by trading partner countries' environmental regulation aimed at internalizing national and global negative environmental externalities, are also among these factors. However, the global climate agenda can not only have a negative impact on export performance, but also generate growth opportunities. The purpose of this study is the econometric modeling of the impact of environmental regulation of trading partner countries on the dynamics of export volumes of Russia's regions based on data for the period of 2013-2020. In addition, the study is aimed at identifying regional factors that determine the sign of the influence of climate regulation of importing countries on export volumes. The study assumes that the effect of climate regulation on export performance is different for the regions of Russia and is determined by institutional and environmental characteristics. The estimation of the gravity equation using the Poisson pseudo-maximum likelihood method for different subsamples of Russia's regions demonstrated that the stringency of environmental regulation of the partner countries is negatively related to the volumes of Russian exports, but there is a positive correlation in the case of regions characterized by favorable conditions for innovation activity and active environmental policy. It was also detected that the regional budget spending on environmental protection do not provide a stimulating effect of climate regulations. Thus, in order to minimize the negative impact of transitional climate risks, special attention of the state should be paid to creating an environment conducive to innovation and the formation of the most effective environmental policy at the regional and national levels. The theoretical significance of the study lies in expanding the traditional gravity model by including the environmental determinants of trade, while the practical significance of the work is represented by recommendations to regional authorities on minimizing the negative impact of transitional climate risks.

The effectiveness of bilateral investment treaties in attracting foreign direct investment: The case of Serbia

Over the past several decades there has been increasing competition among countries to attract foreign direct investment, which is often hypothesised to positively affect the development of host countries. Bilateral investment treaties are one of the policy instruments the host countries often use as a means to encourage foreign direct investment inflows. In this study, we aim to explore the effectiveness of bilateral investment treaties in achieving these goals in the case of Serbia. Using the panel data on Serbia and its 198 partner economies observed in the period 2010-2019, we estimate a gravity model of foreign direct investment inflows by applying the Poisson pseudo-maximum likelihood method. We found that ratified bilateral investment treaties have a statistically significant positive effect on foreign direct investment inflows in Serbia. Furthermore, the quality of the treaties was found to positively affect the inflows, whereby the anti-discriminatory provisions seem to be the most important. The results imply that Serbia could attract more foreign direct investment by concluding new bilateral investment treaties and improving the quality of the existing ones.

COVID-19가 한국의 의약산업 수출에 미친 영향

Purpose – This paper empirically analyzes the impact of the COVID-19 pandemic on Korea’s exports in the pharmaceutical industry, and this estimation result is compared with that of manufacturing. Moreover, to distinguish those impacts between OECD and non-OECD countries, we divide 76 countries into two groups, OECD and non-OECD countries, and compare the estimation results. Design/Methodology/Approach – We used the panel data of 76 countries and quarterly periods from the first quarter of 2020 to last quarter of 2021 for estimation. The econometric technique employed in the study is PPML (Poisson pseudo maximum likelihood). Findings – We show that the COVID-19 pandemic has positively influenced Korea’s exports in the pharmaceutical industry. Moreover, the impact turns out to be statistically more significant in non-OECD countries than OECD countries. The supplementary finding of our study is that there is no clear evidence on the linkage between COVID-19 and Korea’s exports in the manufacturing sector. Research Implications – Unlike existing papers have focused on showing the negative relationship between COVID-19 and international trade, this paper has showed the positive linkage between them.

TURKISH ECONOMY IN THE BELT ROAD INITIATIVE: A GRAVITY MODEL FOR INTERNATIONAL TRADE

In this paper, we attempt to analyze the determinants of international trade flows between Turkey and countries in the One Belt One Road (OBOR) project and their implications for the Turkish economy through the estimation of panel data using a gravity model. In particular, we employ the Poisson Pseudo Maximum Likelihood (PPML) estimation procedure for the nine OBOR nations from the period 2000-2021. This estimator is more robust than other methods such as pooled, fixed, and random models and it is free from the problems of autocorrelation, asymptotic bias, multicollinearity, and heteroscedasticty in the residuals for estimation and inference. First, panel unit root tests show that conducted variables are stationary at the conventional level. Second, the gravity estimations revealed that remoteness, scale, land endowment variables and, dummies (Preferential Trade Agreement and Border) in the gravity model have a positive impact, while GDP Distance and Capital Endowment have an inverse effect on trade flows. Only the language dummy is statistically insignificant. For policy purposes, we concluded that it would be better to promote trade flows with the OBOR countries.

Quality of Indonesia’s domestic institutions and export performance in the era of global value chains

The focus of this research is on analysing the effects of institutional quality and trade agreements on Indonesia bilateral trade in four commodity groups in the era of global value chain (GVC). Employing a panel data gravity model of Indonesian export of four commodities to Indonesia’s trading partners from 2000 to 2018 and estimating the Feasible Generalized Least Squares (FGLS) and the Poisson Pseudo Maximum Likelihood Method (PPML), the results of this study find that institutional quality plays a different role in explaining Indonesia’s export performance of those four commodities, despite the fact that institutions contribute positively. On two commodities that are prospective to increase Indonesia participation in the global value chain, exported intermediates and consumer goods, we find that although both domestic institutions and trading partner institutions are significant to Indonesian export, but we argue that domestic institutions contribute more. This study also reveals that through tariff reductions, Indonesian trade agreements are significant regarding export of all the four commodities group. However, even though tariffs are significant, we find that the quality of institutions, especially domestic institutions, has a greater effect on Indonesia's exports.

DO ICT AND TECHNOLOGICAL DEVELOPMENT FACILITATE SUPPLY CHAIN TRADE?

This paper aims to estimate the impact of ICT and technological development of countries on supply chain trade. As proxy measures of supply chain trade, the author applies domestic value added (DVAFX) included in gross-foreign exports, and foreign-value added included in domestic exports (FVA) from the Eora MRIO database while constructing the ICT variable by using confirmatory factor analysis. Furthermore, as a proxy variable for the country’s technological development, the author applies the economic complexity index developed by Harvard’s Growth Lab, conducting her analysis based on the structural gravity model estimated with the Poisson Pseudo-Maximum Likelihood Estimator (PPML). Together with the standard gravity regressors, the model includes the bilateral position of countries in the supply chain. Our panel dataset covers the 2000-2019 period, including 130 world countries. To control for the potential source of endogeneity, the model includes reporter and partner country fixed effects, yearly fixed effects, and country-pair fixed effects. The results confirm a statistically significant relationship between the country’s technological development and supply-chain trade. Technological development enables a country to produce more complex, higher value-added products and thus to be more upstream positioned in the supply chain. The more upstream the country is in the supply chain, the higher the domestic value added is included in its exports.

The international service trade effects of bilateral investment treaties

AbstractThis paper examines the impact of the bilateral investment treaties (BITs) on a large dataset of service trade using recently developed Poisson pseudo‐maximum likelihood (PPML) estimator regression models with multiple high‐dimensional fixed effects to estimate the structural gravity equations. The model in this paper theoretically demonstrates that BITs reduce service trade from foreign direct investment (FDI) source countries by decreasing the additional variable costs of operating a foreign affiliate. This paper also empirically confirms that BITs decrease service exports from developed to developing economies through analysing a comprehensive WTO‐OECD Balanced Trade in Services Data from 1995 to 2006.

Facilitating trade in intermediate goods

A side effect of economic globalisation and new information and communication technologies is the increasing fragmentation of the production process across different countries and continents, contributing to the rise of trade in intermediate goods, which has increased to almost 2/3 of total world trade. Most of this trade, i.e., intermediate goods, are transported by sea. Maritime trade is one of the most economical but also complex ways of trading and transporting goods, requiring good coordination, various stops and controls, transhipments, storage, ICT technology to track the cargo, etc. Therefore, the objective of this paper is to quantify the impact of trade facilitation on trade in intermediate goods on the sample of EU28 countries, using biennial data for the period 2010-2018. We estimate augmented gravity model on bilateral trade data using a Poisson Pseudo Maximum Likelihood (PPML) estimator. Our results suggest that, as expected, logistics, and in particular ICT development, has a significant and positive effect on trade in intermediate inputs, when controlling for other variables in the gravity model such as GDP of trading partners, distance, contiguity, existence of a free trade agreement, exchange rate, and common cultural proxies. Our results support the global trend of development and investment in logistics, and, in particular, new ICT technologies, which can not only contribute to the continued growth of trade in intermediates, but also help mitigate the negative effects of recent global economic shocks.

Empirical Analysis of Sustainable Trade Effects of FTAs Based on Augmented Gravity Model: A Case Study of China

China has developed many strategies to promote sustainable trade, including accelerating the signing of free-trade agreements (FTAs). However, there is a lack of studies examining the impact of FTAs on the sustainable growth of foreign trade from a holistic perspective. This paper applies an augmented gravity model to verify the trade creation and diversion effects of China’s FTAs that are currently in effect. A panel data analysis over the period of 1995–2019 is conducted on 34 countries and regions, including China, and Poisson pseudo-maximum likelihood (PPML) is employed to test three different fixed-effects models. The results show that the trade effects differ across FTAs, with nine FTAs generally making positive contributions to China’s trade and social welfare growth, and the remaining five FTAs exhibiting varying degrees of trade diversion or contraction effects. Empirically, it is clear that participation in FTAs has contributed to the sustainable trade of China, but China still needs to take prudent action to pursue further trade liberalization in order to counter the potential threat of trade diversion.

Assessing the Impacts of Non-Tariff Measures on the Export of Vietnam’s Main Agricultural and Seafood Products

With the development of free trade agreements, tariff barriers are gradually removed, and non-tariff measures are playing an important role in the trade policies of countries. However, studies on the effects of non-tariff measures on trade show a great disparity in results and both negative and positive influences can be found when non-tariff measures are imposed in different contexts. The heterogeneity in the result is often hypothesized to be the consequence of intrinsic characteristics related to products and countries; therefore, arguably, unbiased and reliable estimation of non-tariff measure effect on trade should be analyzed in product level data for a specific country. Hence, the study attempts to use the gravity model and Poisson Pseudo-Maximum Likelihood estimation (PPML) to quantify the effects of non-tariff measures on the export of some agricultural and seafood products of Vietnam to certain main markets including the United States (US), European Union (EU), China, and Japan. The research findings show that from a national perspective, non-tariff measures mostly have a negative impact on agricultural exports, especially sanitary and phytosanitary measures (SPM), and countervailing measures (CM). In terms of commodities, coffee and seafood are particularly sensitive to non-tariff measures, while other key agricultural product groups are mostly affected by tariff measures.