Poisson Pseudo Maximum Likelihood Research Articles

Assessing the impact of non-tariff measures on Sri Lankan mango exports: insights, challenges, and recommendations

IntroductionWith the increase in non-tariff measures (NTMs) in recent years, understanding their impact on trade policies and agricultural exports is of utmost importance for countries like Sri Lanka, where the proliferation of NTMs has posed substantial impediments to its mango export industry. However, studying NTMs can be challenging due to their complex nature, diverse range, and limited information availability.MethodsThis research aims to investigate the significant effect of NTMs on Sri Lankan mango exports, identify the pivotal drivers influencing mango exports, and analyze the performance of mango exports in Sri Lanka. This study utilized a panel dataset of 16 importing countries spanning the period from 2000 to 2021. The primary focus was on examining NTM-related challenges and obstacles faced by the mango export industry in Sri Lanka. The identification and quantification of these obstacles were achieved through a multifaceted approach in which assessment of NTM-related rejections, both domestic and overseas, evaluation of NTM incidences using frequency and coverage ratio measures, and the deployment of various gravity model equations to quantify the effect of NTMs were taken into consideration. Probit, Ordinary Least Square, Random Effects, and Poisson Pseudo Maximum Likelihood estimation techniques were utilized for data analysis.ResultsThe findings indicate a significant inverse correlation between the increase in the total count of NTMs and Sri Lankan mango exports if the country aims to export more mangoes to relevant markets, while Sanitary and Phytosanitary Measures (SPS), Technical Barriers to Trade (TBT), and Pre-shipment Inspection (PSI) contributed to increased mango exports. Among other explanatory variables, the GDP of both importing and exporting countries had a positive influence on Sri Lankan mango exports. Surprisingly, the distance to the importing country had no significant effect, though it shows a negative sign.DiscussionThis study provides valuable insights into the impact of NTMs on Sri Lankan mango exports. It highlights the considerable influence of NTMs on the overall fresh fruit export sector. We recommend proactively aligning internal quality testing regulations with the standards required by destination countries to promote future expansion.

The more the better? How degree programs’ variety affects university students’ churn risk

Students’ intra- and, especially, inter-degree relocation poses significant challenges that tertiary education systems and universities must address to identify the best possible solutions for its reduction. Indeed, this phenomenon has a major impact on several aspects, from the reallocation of financial resources to factors related to the organization of spaces and activities, as well as in terms of human and social capital. Moreover, it is much more challenging when involving different universities in different geographical areas. This paper addresses the issue of churn risk among students and its relationship with the institutions’ educational offerings, in terms of degree programs, by accounting for the impact of the characteristics of both universities and hosting areas. In particular, the analysis relies on Italian administrative data regarding students who decide to change university or field of study when enrolling in their second year of career. The results obtained performing the Poisson Pseudo Maximum Likelihood estimation show that the variety and the dimension of universities’ services supply contribute to reducing students’ churn risks and are positively associated with universities’ retention rates.

Do export responses to exchange rate movements differ in micro export flows?

This paper empirically examines how exports respond to exchange rate movements (exchange rate and exchange rate volatility) at the micro and macro levels using Turkey’s bilateral export data with 65 partner countries. Panel data contaninig 65 cross-sectional dimensions and 60 monthly time series dimensions from 2018:01 to 2022:12 are used. The empirical results of the Poisson Pseudo Maximum Likelihood (PPML) technique show that the negative effect of exchange rate volatility on micro export flows is amplified. Moreover, the potential positive effect of the exchange rate on micro export flows is weaker. Our findings are robust against the alternative method of exchange rate volatility and nominal exchange rate volatility. Our results are also intact under alternative robustness tests. The paper provides notable policy implications. Policymakers should be aware of the potential structural differences between micro and macro exports. Therefore, policymakers should also consider other aspects such as cross-border e-commerce when formulating economic policies on microexports.

Institutional quality and emigration nexus: Empirical evidence from Türkiye

AbstractThis study attempts to fill an important gap in the empirical literature by investigating the impact of institutional quality in destination countries on emigrants from Türkiye using bilateral migration data from 2010 through 2020. For this purpose, the study builds an augmented gravity model, including economic, geographic, and cultural variables in an exponential form and estimates it by the Poisson Pseudo Maximum Likelihood (PPML) method. Empirical results significantly confirm the pulling role of strong institutions in destination countries for emigrants from Türkiye since all institutional quality indicators are positively associated with emigrant movements, albeit just one of them, regulatory quality, is statistically insignificant. Among indicators of institutional quality, the most pulling ones for emigrants are voice and accountability and the rule of law, followed by government effectiveness, control of corruption, and political stability and absence of violence, respectively. Overall results indicate that institutions are front‐line players in the emigrants' migration decision and destination choice process. In this context, policy‐makers in both Türkiye and the destination country may implement an institutional policy considering the outcomes stemming from migration movements.

Economic geography of talent migration and agglomeration in China: A dual-driver framework

The long-standing debate on the role of economic factors and amenities on talent migration and redistribution foreshadows the importance of spatial economic theoretical thinking in resolving the effects of duality, a point yet to be conclusively addressed in the existing literature. Situated within the framework of new economic geography (NEG), this article introduces an innovative theoretical model – the Dual-Driver (DD) framework– aiming at comprehending the nuanced dual impact of economic and amenity factors on talent movements between regions. While the DD framework retains the mechanisms of increasing returns to scale, iceberg transportation cost, and talent agglomeration presented in the NEG models, it depicts, for the first time, the self-reinforcing mechanisms between non-traded goods (i.e., amenities) and talent agglomeration. The model describes a logic of talent movements influenced by the dual drivers of regional economic factors (nominal wage, the diversity of local manufacturing products) and amenities (the diversity and quality of amenities, transfer payment for talent), among which the economic effects play a predominant role versus the amenity effects. Empirical evidence has been given by the geographical analysis of China's internal talent migration between 2000 and 2015 and the corresponding econometric analysis using the Poisson pseudo-maximum likelihood (PPML) estimation. Our findings furnish a theoretical perspective for comprehending talent geography and offer policy insights into China's logic of talent migration.

Unravelling open innovation determinants and firm performance relationships in CEE and SEE countries

Purpose Open innovation (OI), by now one of the major concepts for the analysis of innovation, is seen as a methodology for collaboratively designing and implementing solutions by engaging stakeholders in an iterative and inclusive service design process. This paper aims to empirically investigate OI capacities, defined as a cooperative, knowledge-sharing innovation ecosystem, and to explore how it can lead to improved performance of firms in Central and Eastern European (CEE) and Southeastern European (SEE) countries.Design/methodology/approach The study builds on the World Bank/European Bank for Reconstruction and Development (EBRD’s) Business Environment Enterprise Performance Survey (BEEPS) dataset for 2009, 2013 and 2019. Primarily, the research model was estimated using log-transformed ordinary least squares (OLS). Taking into consideration that this method might produce substantial bias, yielding misleading inferences, this study is fitting Poisson pseudo maximum likelihood estimators with robust standard errors and instrumental variable/generalized method of moments estimation (IV/GMM) approach for comparative results. Secondarily, the research model was tested using structural equation modelling (SEM) to investigate the relationship between five OI capacities and firm performance.Findings The findings indicate that there is a significant positive relationship between most OI capacities and firm performance, except for innovation, which did not show a statistically significant relationship with firm performance. Specifically, research and development (R&D), knowledge and coopetition are statistically significant and positively associated with firm performance, whereas transformation is statistically significant but negatively associated with firm performance. The IV/GMM estimations’ findings support the view that the firm performance is significantly affected by OI capacities, together with some control variables such as size, age, foreign ownership and year dummy to have a significant impact on firm performance.Originality/value This paper fills an identified gap in the literature by investigating the impact of OI on firm performance executed in the specific CEE and SEE country context.

Effects of logistics performance on Vietnam’s exports: a quantitative analysis using the PPML method

This study aims to analyze the effects of logistics performance on Vietnam’s exports at both the overall level and in specific aspects. We investigate the linkage between logistics performance and Vietnam’s exports based on a panel of bilateral trade from Vietnam to 158 trading partners from 2007 to 2018. Using the Poisson pseudo-maximum likelihood method, the positive and significant effects of Vietnam’s and importing countries’ logistics performance on exports are identified. Our estimates become highly consistent after controlling for both time-specific effects and time-invariant country-fixed effects and remain robust to changes in the model specification, contributing reliable empirical evidence to the literature. Considering the specific aspects of logistics performance, we find the significant roles of the ability to track and trace consignments, the quality of logistics services, the customs clearance efficiency, and the timeliness of shipments in trade. From Vietnam’s perspective, improvements in tracking and tracing ability and timeliness can enhance exports to other countries, with larger effects than those of trading partners. Based on these findings, this study provides evidence for policymakers to effectively enhance trade with other countries by developing the national logistics system alongside further logistics cooperation with trading partners and with a greater focus on tracking and tracing ability and timeliness.

How Social Networks Shape Refugee Movements in Wartime: Evidence from the Russian Attack on Ukraine

This article analyzes the key factors guiding the destination choice of Ukrainian refugees in the EU between March and December 2022 in the framework of the activation of the Temporary Protection Directive. To this end, it specifies a migration model, computed for the whole period and two subperiods (March–May and June–December), that captures the influence of social networks. Furthermore, our migration model makes a distinction for the first time between prewar migrant communities and the new social networks that are emerging in wartime circumstances. The estimation of the model, using the Poisson Pseudo-Maximum Likelihood estimator by Santos Silva and Tenreyro (2006), confirmed the importance of both types of social networks in explaining refugees’ choice of destination. The results also revealed that some economic variables (expected earnings and the size of the informal sector) influenced the location choice of refugees since the outbreak of the war, while other socioeconomic and political factors (risk of social exclusion, anti-immigration sentiment, and rule of law) only did so after a few months, when it became increasingly self-evident that the war was going on for a long time.

Does financial development and institutional quality matter in South-South Trade? Evidence from Sub-Saharan Africa

This study re-evaluates the determinants of international trade in the global south, focusing on intra- and extra-SSA trade while considering financial development and institutional quality as additional predictors. It also examines whether these factors differ for south-south and north–south trade ties. We used a 22-years (ranging from 2000 to 2021) panel of 98 countries (41 from the SSA and the remaining from the ROW). A panel gravity model with Poisson pseudo-maximum likelihood (PPML) estimation is used for the analysis. The results show that financial development in origin and destination countries boosts intra-trade in SSA countries, and the developed financial sector of the destination countries contributes to both intra-bloc and international trade. Financial development of exporting countries also spurs intra-bloc trade in SSA countries and the global south. In addition, apart from common expectations, the institutional quality of exporting countries plays a deterrent role, while the institutional quality of destination countries plays a positive and significant role in trade in the global south. We identified the interaction term for financial development and institutional quality of the exporting countries with a significant and positive coefficient for the global south and the global north, and null for intra-SSA trade. For destination countries, it becomes significantly positive with SSA and the global south but negative with the global north. The findings suggest that as part of the policy measures to boost intra-bloc trade in SSA and the global south, ensuring financial development needs better emphasis.

Deep trade agreements and services trade: An analysis based on service trade provisions

AbstractOur paper builds a novel panel data sourced from the Regional Trade Agreements Database and Database on International Trade in Services Statistics (ITSS) to explore the heterogeneous effects of service trade agreements on services trade. Then we employ a gravity model with the Poisson pseudo‐maximum likelihood (PPML) estimation and obtain the following findings: First, both general service trade agreements and deep service trade agreements promote services trade. Yet, deep trade agreements have a higher trade‐expansion effect (roughly 21.53%) on services trade compared to general ones (16.9%). Next, based on the content of trade‐related provisions, we find provisions of rights of non‐establishment and natural person movement largely increase the services trade, while review provisions do not have a significant impact on services trade. Surprisingly, provisions with MFN status even exhibit a negative relationship with services trade. Third, with whom you sign the agreements matters. Deep trade agreements exert a positive and significant impact on services trade between high‐income countries (NN), low‐income countries (SS) and high‐ to low‐income countries (NS), but are insignificant between low‐ to high‐income countries (SN). Four, emerging regions, including China, may benefit more from deep trade agreements. As indicated by propensity score matching, deep trade agreements reduce service trade costs and improve the business environment more effectively than GTAs. Our empirical results are robust after controlling for the endogeneity of DTAs and GTAs. Our findings provide direct evidence for the role of deep service trade agreements in fostering international economic integration.

Do unpriced natural and ecosystem capital affect economic output? Growth regression analyses

AbstractServices provided by nature and ecosystem capital are unpriced and their contributions cannot be observed through factor payments. Estimates of nature's gross domestic product contribution are thus based on bottom‐up extrapolations of local ecological valuations or various sectoral dependency assumptions. These estimates are hence partial and wide‐ranging. On the other hand, omission of nature and ecosystem capital in standard growth regressions potentially biases estimated returns to other factors of production. This paper incorporates various categories of natural capital and biodiversity into growth regressions, with annual data covering more than 100 economies over more than two decades. A range of econometric specifications are used, including fixed effect panel regressions, Arellano and Bond, and Pseudo Poisson Maximum Likelihood. The estimates point to natural capital, especially the narrower and specific ecosystem capital, having a sizeable positive elasticity of around one‐third of total gross fixed capital. Ecosystem capital is thus estimated to contribute around USD6–12 trillion (or 10–20 trillion in purchasing power parity terms) annually for the global economy. This estimated contribution is significantly higher than what is implied by existing stock valuations, underscoring the importance of ecosystem capital to sustainable growth.

Analysing the Nexus between the Financial Sector and Economic Growth in Nigeria: A Comparative Investigation using, BVAR, Linear Regression (OLS), and PPML Models

Aims: This study aims to analyze the complex relationship between the financial sector and economic growth in Nigeria. The study aims to provide comprehensive insights into this nexus by employing a comparative investigation using three distinct models: Linear Regression, Poisson Pseudo Maximum Likelihood (PPML), and Bayesian Vector Autoregression (BVAR).
 Methodology: The study then applied three different models, with a specific focus on the BVAR(2) model, supported by various diagnostic tests and stability assessments. The inclusion of Linear regression analysis and Poisson Pseudo Maximum Likelihood Estimator (PPML) enhances the depth of the study, providing nuanced insights into the impact of specific financial sector variables on economic growth.
 Results: The BVAR (2) model emerges as the optimal choice, demonstrating its reliability in capturing dynamic interactions and offering a powerful tool for policymakers. Specific results, such as the significant negative impact of D(CPS) in the regression analysis and the high R-squared in PPML, provide actionable insights into areas requiring policy interventions and underscore the substantial contribution of the financial sector to economic growth.
 Conclusion: The comparative assessment of model performances, favoring the BVAR model, guides future research and policy considerations, providing a reliable framework for further investigations. The study's insights are positioned as valuable for policymakers seeking to enhance economic growth through strategic interventions in the financial sector. Overall, the abstract succinctly encapsulates the aims, methodology, results, and concluding implications of the study on the nexus between the financial sector and economic growth in Nigeria.

Strategy for Increasing Exports Through ICT Development and Potential Market Mapping: Case Study of Indonesia Labor Intensive Industries

Purpose: This research aims to specifically identify the role of ICT in the export performance of Indonesia's la-bor-intensive industries and Mapping potential market for Indonesia's labor-intensive industries export.
 Design/methodology/approach: The analysis was carried out by developing a gravity model and estimated using the Pseudo Poisson Maximum-Likelihood (PPML) and Generalized Method of Moment (GMM) methods as robust-ness tests.
 Findings: The estimation results show that ICT, both from the quantity aspect and the quality aspect, has a positive and significant impact on the volume of Indonesian exports. The results of this estimation have been proven to be consistent through several tests by controlling the problems of endogeneity, simultaneity, and auto-correlation.
 Research limitations/implications: The model developed in the study tends to interact with variables from both countries, namely Indonesia as an exporter country and a partner country for importing Indonesian products. The application of this kind of interaction causes the results of the interpretation to be unable to specifically explain the effect of variables in each country.
 Originality/value: This study discussed the impact of ICT through the quality and quantity aspects, this study also used product-level data, so the interpretation results more specifically explained the impact of ICT. Further analysis in this study also contributes significantly to identifying which partner has a potential market as the main destination of Indonesia's exports.

The effect of FDI regulatory barriers: evidence from OECD countries

ABSTRACT This study aims to analyse the impact of the OECD FDI Regulatory Restrictiveness Index on actual FDI (Foreign Direct Investment) flows into the 38 OECD member countries. Using PPML (Poisson Pseudo Maximum Likelihood), GLS (Generalized Least Squares method), and Heckman’s sample selection estimator, this paper undertakes to identify the impact of FDI Regulatory Restrictiveness Index on FDI inflows to all OECD member countries from 129 partner countries from 2006 to 2021. It finds that the overall level of restrictions, screening and approval measures, and other operational restrictions all have a statistically significant negative sign, except for equity restrictions (ER). This suggests that the higher the level of restrictions on FDI, the less direct investment flows into OECD countries. In other words, liberalizing or reforming FDI restrictions can lead to an increase in inward FDI. Moreover, results show that the impact of even small regulatory relaxations is not negligible. While previous studies have mainly analysed the determinants of FDI inflows based on theories from the investor (supplier) perspective, this study differs in that it provides a reference analysis of FDI policies and laws from the host country’s (demander) perspective, in which areas and to what extent they need to be liberalized.

Global energy transition and foreign environmental regulations: Impacts on Russian regions’ export volumes

This paper analyses the impacts of trading partners’ environmental regulation on the export volumes of the Russian regions, using panel data covering about 140,000 observations in 84 Russian regions and 204 countries for the period 2013–2020. We employ the Gravity Model of international trade and Heckman Sample Selection methodology, with the fixed effects and random effects Poisson Pseudo-Maximum Likelihood techniques to analyse two subsamples of the Russian regions with different shares of environmentally sensitive goods in regional exports. As a robustness check, we utilize the non-parametric Driscoll–Kraay approach. The results of the econometric estimation demonstrate that environmental regulations enhance the export of regions with a high share of environmentally sensitive goods in export structure, while for the rest of the regions the environmental regulations negatively affect export volumes. The promoting effect is associated with a higher level of innovativeness of the regions and the role of the global energy transition process. We conclude that the environmental agenda is a challenge for some Russian regional exporters due to the lack of own environmental regulation, and to the specific features of the commodity and geographic structure of exports. To transform the negative impact into the positive one for all Russian regions, policy measures are necessary on the federal, regional, and company levels, encompassing environmental regulations and green development strategies, along with innovation and cluster policies, and the development of human capital and infrastructure.

Deploying Machine Learning Methods to Predict Global Trade Patterns: The Case of Beef

Highlights Machine Learning (ML) methods are offered as an alternative to conventional techniques for understanding global commodity trade. A formal comparison is made between ML results with those from the Poisson Pseudo Maximum Likelihood (PPML) Estimator, which is the most commonly used statistical technique for bilateral trade analysis. PPML takes into account fixed effects and the dynamic nature of panel data to provide a better fit and higher prediction accuracy than ML in the context of in-sample forecasts. ML methods have strengths in feature selection, better validation statistics, and stronger predictive power than PPML, especially with out-of-sample forecasts. Abstract. In international economics, there has been a steady stream of innovations to explain patterns of trade between and among countries with emerging techniques. The most recent - Poisson Pseudo Maximum Likelihood (PPML) estimator – corrects for a potential bias caused by the large proportion of zero observations in bilateral trade data. Alternatively, this study offers Machine Learning (ML) as an option, especially in the presence of finer data on bilateral trade patterns. Using monthly and HS-6-digit (product) level data, the study finds that the main advantage of PPML is its accuracy of forecasts in-sample, but feature selection is somewhat rigid due to the inclusion of a large number of pair-wise fixed effects. ML models have the advantage in selecting features when a long list of explanatory variables is to be considered. Model validation statistics such as MAE and RMSE favor ML methods, but PPML tends to yield higher goodness of fit. In the out-of-sample context, ML has better accuracy than PPML, and a one-step walk-forward ML approach further improves the accuracy of ML forecasts. While PPML has a rich research and application history, emerging ML techniques have sufficient room for improvement in their adaptation to economic analysis. Keywords: Beef, Bilateral Trade, Boosting, Machine learning, ML for Policy

Economic, geographical, institutional, and political determinants of bilateral manufacturing exports: A structural gravity model approach for Türkiye

The study investigates the economic, geographical, institutional, and political determinants of T?rkiye?s bilateral manufacturing exports for 2003-2018, applying the structural gravity model and considering 30 main export partners of T?rkiye. The Poisson pseudo maximum likelihood method results reveal that T?rkiye?s manufacturing exports are mostly directed by its own and partners? economic sizes. While common borders and cultural similarity positively impact manufacturing exports, distance and landlocked position affect it negatively. The degrees of institutional quality, trade freedom in T?rkiye, and membership of the partner countries in the World Trade Organization are resistance factors against manufacturing exports, whereas trade agreements encourage it. As the bilateral or multilateral trade agreements turned out to be the driving forces of manufacturing exports, T?rkiye should sign additional trade agreements and/or amplify trade agreements that have already been signed rather than standard trade policy implementations.

Determinants of high-tech export: evidence from a cross-country analysis

Relevance. The adoption of new technologies and the rapid emergence of innovation spur high-tech production and export-led economic growth. We aim to provide fresh evidence on the determinants of high-tech exports, considering different macroeconomic factors within the framework of the gravity model. Research Objective. The aim of the research is to empirically assess the impact of macroeconomic instability, tax policies, natural resources endowment, human capital, and institutional environment on the promotion of high-tech exports. Data and Methods. In considering the institutional indicator, six distinct indices from the World Bank are examined, and a common indicator is computed using principal component analysis. The econometric modeling uses a panel dataset covering the world's 80 largest economies from 1996 to 2019. To test the assumptions of the gravity model and tackle the heteroscedasticity problem, the Poisson Pseudo Maximum Likelihood methodology is employed. Results. Higher inflation and unemployment rates are found to significantly decrease high-tech exports, while government external debt contributes to their enhancement. Tight tax policy and an increase in tax contribution are counterproductive in spurring high-tech exports. A negative and significant result is found for resource endowment, indicating that an increase in resource exports is counterproductive for technological advances and high-tech production. In most cases, the institutional environment and human capital significantly promote high-tech exports. Conclusions. Based on the presented empirical findings, we offer recommendations for the government to stimulate high-tech exports.

DETERMINANTS OF VIETNAM’S AGRICULTUAL EXPORTS, FOCUSING ON ITS TRADING PARTNERS’ CHARACTERISTICS

This study investigates the determinants of Vietnam’s agricultural exports, focusing on its trading partners’ characteristics. The author adopts Poisson Pseudo-Maximum Likelihood estimators to estimate a gravity model covering bilateral agricultural exports from Vietnam to 187 of its trading partners during 1996-2021. The empirical results reveal that exchange rate volatility and geographical distance hamper exports, while regional trade agreements (RTAs), shared borders, and dependent relationships in the past boost exports. When considering the features of importing countries, I find that population, GDP per capita, policy stability, and financial development are crucial in promoting Vietnam's agricultural exports. The findings of this study imply that it is necessary to maintain stable exchange rates and actively join RTAs to increase the agricultural exports of Vietnam. Moreover, to enhance agricultural exports, exporting firms should target trading partners in countries with large economic size, high per capita income, good governance quality, developed financial markets, or those who share a common border or have ever in dependent relationship with Vietnam.

Energy security, governance quality, and economic performance in sub-Saharan Africa

This study investigates the role of energy security and governance quality in economic performance using 22 sub-Saharan African countries between 2000 and 2020. It explores Poisson Pseudo-maximum Likelihood Estimator. More so, five measures of energy security (accessibility, affordability, acceptability, availability, and developability) and four measures of governance quality (political, economic, institutional, and aggregate) are considered. The results show that only the availability and developability of energy security significantly and positively enhance economic performance. Other measures have little or no effect on economic performance. Additionally, measures of governance quality largely and positively facilitate economic performance. On interaction terms, governance quality was found to significantly enhance the effectiveness of the availability aspects of energy security on economic performance. However, the governance structure is still very weak to foster the effectiveness of other aspects of energy security in the growth process. Thus, countries need to be proactive in strengthening their governance structures to harness the benefits associated with energy security for sustainable economic growth. Specifically, policymakers need to prioritize policies that will enhance energy availability and developability, promote energy sustainability and equality, disincentivize high-emission energy sources, strengthen governance roles in energy security, and mitigate oil price volatility.