Pseudo Maximum Likelihood Research Articles

Two-stage pseudo maximum likelihood estimation of semiparametric copula-based regression models for semi-competing risks data.

We propose a two-stage estimation procedure for a copula-based model with semi-competing risks data, where the non-terminal event is subject to dependent censoring by the terminal event, and both events are subject to independent censoring. With a copula-based model, the marginal survival functions of individual event times are specified by semiparametric transformation models, and the dependence between the bivariate event times is specified by a parametric copula function. For the estimation procedure, in the first stage, the parameters associated with the marginal of the terminal event are estimated using only the corresponding observed outcomes, and in the second stage, the marginal parameters for the non-terminal event time and the copula parameter are estimated together via maximizing a pseudo-likelihood function based on the joint distribution of the bivariate event times. We derived the asymptotic properties of the proposed estimator and provided an analytic variance estimator for inference. Through simulation studies, we showed that our approach leads to consistent estimates with less computational cost and more robustness than the one-stage procedure developed in Chen YH (Lifetime Data Anal 18:36-57, 2012), where all parameters were estimated simultaneously. In addition, our approach demonstrates more desirable finite-sample performances over another existing two-stage estimation method proposed in Zhu H et al., (Commu Statistics-Theory Methods 51(22):7830-7845, 2021) . An R package PMLE4SCR is developed to implement our proposed method.

Regional integration and export performance of Pakistan: Empirical evidence from the Shanghai Cooperation Organization (SCO).

The study examines export impact of Pakistan's integration into Shanghai Cooperation Organization (SCO) on its export's performance. We apply Poisson Pseudo-Maximum Likelihood (PPML) on augmented gravity model to estimate trade data from the period before and after permanent membership with Shanghai Cooperation Organization in 2017. The study aims to explore changes in exports volume and analyze the key mechanism through which Shanghai Cooperation Organization promotes exports. The study assesses that after integration which key exports sector such as agriculture or manufacturing sectors are affected more significantly. The initial findings suggest that SCO integration positively affect and provide access to Central Asian markets, leading to modest but noticeable promotion in exports promotion. In heterogeneity analysis we find that exports of Pakistan are more significant with low and middle-income level countries compared to higher-income level countries. Additionally, exports in the manufacturing sector benefited more than in the agriculture sector. The significant and positive findings of mechanism analysis indicate that the belt and road (B&R) initiative and bilateral trade agreements are the key factors to enhanced exports. The overall impact remains moderated by structural changes in Pakistan economy, such as poor infrastructure, deficiency in energy sector and limited trade relations with its neighbors India and Iran. The study concludes that although the SCO integration has positively promoted exports of Pakistan however, it requires to address domestic economic constraints and capitalize more effectively the benefits of SCO membership through regional cooperation mechanism. For more potential benefits in the region SCO needs to expand B&R connectivity, encourage more trade agreements, and adopt favorable environment to attract high income countries in the organization. The study provides the base for future research in depth analysis of long-term impact of SCO integration on Pakistan exports.

Impact of Ebola Virus Disease and ECOWAS Membership on Intra-Regional Trade in West Africa

The West African sub-region bore the brunt of the world's largest Ebola outbreak, significantly impacting the economic activities and trade shares of the affected countries. This study seeks to examine the repercussions of the Ebola Virus Disease (EVD) on the trade shares of affected countries and to explore the potential influence of ECOWAS membership on intra-regional trade in West Africa. Using the Poison Pseudo Maximum Likelihood (PPML) estimation technique, an analysis of the augmented gravity model of international trade was conducted. The findings indicate a two-fold reduction in the trade shares of affected countries with their intra-regional partners due to the Ebola Virus Disease. Additionally, with Mauritania expressing its desire to join the ECOWAS sub-region, there is a need to explore the impact of the Regional Economic Community on intra-regional trade. Furthermore, the study reveals that ECOWAS membership has the potential to double trade levels in West Africa. The findings also suggest that Mauritania stands to gain significant benefits from becoming a member of the ECOWAS. In conclusion, this study highlights the necessity for ECOWAS to proactively respond to disease outbreaks and underscores the importance of increased research investment. Moreover, it emphasizes the need for the ECOWAS to further improve infrastructure to facilitate intra-regional trade, especially in transportation.

한국의 대외 수출에 미치는 TBT와 미통보 기술 규제의 영향분석: 중력모형과 PPML 방법론을 통한 접근

This study investigates the impact of Technical Barriers to Trade (TBT) and unnotified technologies on South Korea’s foreign exports, analyzing the background and objectives. With the expansion of regional economic blocks such as FTAs, the EU, and NAFTA, the scope of non-tariff barriers, including TBT and Sanitary and Phytosanitary (SPS) measures, has broadened. These non-tariff barriers, often implemented for safety purposes like environmental protection, can increase shipping and compliance costs, imposing a burden on domestic industries. The main objective of this study is to quantitatively evaluate the effects of TBT and unnotified technologies on South Korea's exports across various industries from 1995 to 2022. To achieve this, we employ the gravity model, one of the most widely used models in explaining trade conflicts, alongside the Poisson Pseudo Maximum Likelihood (PPML) method, which is suitable for handling the complexities of trade data with zero trade flows. This approach enables a detailed analysis of the impact of TBT and unnotified technologies on export performance, disaggregated by objective and industry. The results reveal that while TBT has a positive effect in promoting exports, unnotified technologies have a negative impact. These findings highlight the importance of distinguishing between the two in international trade negotiations.

The gravity of distance: evidence from a trade embargo

Abstract On 5 June 2017, an airspace blockade was imposed on the State of Qatar by Bahrain, Saudi Arabia, United Arab Emirates (neighboring countries), and Egypt. We exploit this exogenous increase in air transportation costs toward non-blockading countries to examine the effect of increased travel distance, due to re-routing, on bilateral trade. Based on a gravity model estimated using a Poisson pseudo-maximum likelihood estimator, we find a distance elasticity of imports between −0.3 and −0.5. Overcoming the limitations of cross-sectional studies and taking advantage of this quasi-natural experiment, our findings are robust and revise downward previous estimates of the distance elasticity.

Determinants of China’s technological trade flows with Central Asian countries (CACs): a panel gravity approach

The purpose of this study is to examine the determinants of Chinese technological trade flows with Central Asian countries (CAC) with a revealed comparative advantage and the gravity model using two estimation techniques. The present study employs the Ordinary Least Square (OLS) and the Poisson pseudo-maximum likelihood (PPML) on the data set from 2003 to 2018 panel dataset. Results from the Gravity model demonstrates that low-tech, medium-tech, and high-tech trade flows boost economic development in China and Central Asian nations, adversely affecting all technology trade flows in geographical distance. The research indicated that exchange rates showed a negative indication in bilateral trade, medium-tech trade, and high-tech trade. In contrast, the low technology trade showed a positive flow between China and Central Asia. Furthermore, the results reveal that openness to trade and membership of the WTO show a positive indication. The trade openness policy on both sides thus has a major beneficial effect on trade volumes. It proposed increased liberalization of trade policy and greater involvement in global commerce. In addition, Central Asia and export industries should take additional initiatives to enhance and diversify high-tech exports. A competitive international market provides perfect equality in reciprocal trade interactions.

Effect of Fintech on Sustainable Development Goals: An Empirical Analysis

Abstract This paper empirically examines the impact of financial technology (FinTech) and financial inclusion on sustainable development goals (SDGs). The adoption of FinTech has a significant positive effect on key SDGs in developing nations. Specifically, FinTech contributes to reducing income inequality and poverty, while promoting gender equality, access to basic sanitation, clean energy, and education. Additionally, the increasing adoption of FinTech is linked to overall economic growth. To address potential biases from heteroscedasticity and endogeneity, we conduct robustness checks using simultaneous equation modeling and Poisson pseudo-maximum likelihood estimations. Our findings confirm that the benchmark results are robust. JEL Codes: O1, O19, O20, Q01. Keywords: Sustainable Development Goals, SDG, Fintech, Financial Inclusion, Pseudo – Poisson Maximum Likelihood (PPML), Simultaneous Equations Model (SEM).

Parametric and semiparametric approaches for copula-based regression estimation

Based on the normality assumption on dependent variable, regression analysis is one of the most popular statistical techniques for studying the dependence between response and explanatory variables. However, violation of this assumption in the data makes regression analysis inappropriate in several real life situations. Copula is a powerful tool for modeling multivariate data and have recently been employed in regression analysis. The key concept behind copula-based regression approach is to formulate conditional expectation in terms of copula density and marginal distributions. In this paper, we explore parametric and semiparametric estimations of the copula-based regression function. The maximum likelihood (ML), inference functions for margins (IFM), and pseudo maximum likelihood (PML) techniques are adopted here for estimation purposes. Extensive numerical experiments are performed to illustrate the performance of the proposed copula-based regression estimators under specified and misspecified scenarios of copulas and marginals. Finally, two real data applications are also presented to demonstrate the performance of the considered estimators.

How Product Standards Influence Tea Exports? Empirical Evidence from India

India has witnessed a declining trend in tea exports in the recent period, which can partly be attributed to competition from exporters (e.g., Kenya and Sri Lanka) enjoying price advantages over the Indian varieties. However, although after the inception of the World Trade Organization (WTO) in 1995, the tariff barriers on Indian tea exports have come down across developed partners, the incidence of non-tariff barriers (NTBs) has emerged as a challenge in many destinations, with a possible dampening effect on exports. The present analysis attempts to analyse whether the imposition of product standard related measures, particularly sanitary and phytosanitary (SPS) and Technical Barriers to Trade (TBT) interventions, may have negatively influenced Indian tea exports over the period 1996–2021. Rather than considering the mere presence of SPS–TBT standards in major partner countries, their potential impacts on Indian tea exports have been determined by analysing the stringency levels of the corresponding notifications submitted to the WTO. The constructed stringency patterns are then incorporated into the Poisson pseudo maximum likelihood estimation models. The observed negative influence of standard-related measures in partner countries on Indian tea exports calls for policy interventions to enable the sector to better ensure compliance in the future.

Environmental, Geographical, and Economic Impacts of Inbound Tourism in China: A Mixed-Effects Gravity Model Approach

This study examines the dynamics of inbound tourism in China, utilizing a mixed-effects gravity model to analyze data from urban clusters around China’s three major airports. The research methodology of the study includes applying advanced econometric techniques, such as the Poisson pseudo-maximum likelihood estimation, to ensure robust and accurate results. The study focuses on international tourist arrivals and foreign exchange earnings, identifying key drivers such as tourism resources, transportation safety, and service quality. Our findings indicate a 10% increase in per capita GDP correlates with a 0.88% rise in inbound tourist numbers. Additionally, proximity to major urban centers like Beijing, Shanghai, and Guangzhou significantly influences tourist arrivals, with every 100 km increase in distance resulting in a 5.56% decrease in tourist numbers. The study also explores the impact of environmental factors on tourism, suggesting that improvements in green coverage and reductions in industrial waste and traffic fatalities could enhance tourist arrivals. Conversely, environmental protection measures can both positively and negatively impact tourism. This research provides a strategic blueprint for policymakers and professionals in tourism and environmental sustainability, emphasizing the importance of integrated environmental sustainability in tourism development strategies. The model accounts for up to 79% of the variability in inbound tourism flows, offering robust evidence that economic and policy dimensions impact tourism.

Kinerja Ekspor Produk Teh Indonesia di Pasar Internasional: Asesmen Perjanjian Perdagangan Indonesia

The decline in Indonesian tea products export performance does not correspond to the Government initiatives to reduce barriers through trade agreements. This research aims to analyse the export performance and the role of trade agreements towards Indonesian tea products export. This study employs panel data regression with a 15-year time series (2007-2021) and a cross-section of 40 destination countries. The data are analysed using a modified export approach gravity model with Poisson Pseudo-Maximum Likelihood (PPML) estimation. The research results show that the Indonesian tea products export destinations are dominated by Asia (19 countries) and Europe (12 countries). The regression results suggest that the implementation of trade agreements with Asian and European region countries has not effectively increased Indonesian tea products export. On the other hand, the implementation of trade agreements with other region countries, i.e., Australia and New Zealand, has successfully promoted export towards Indonesian tea products. Those can be attributed to trade agreements underutilization and trade barriers imposed by the trade agreement members. Hence, inward and outward-looking strategies are necessary to promote the export creation effect of implemented trade agreements towards Indonesian tea product exports.

The Role of Time Zone Differences on Bilateral Service Flows from Kenya

ABSTRACT This study investigates the effect of time zone differences on service exports (total and nine categories—travel, transport, computer and information, construction, financial, insurance, government, other business services, and personal, cultural, and recreational services) from Kenya. Estimates from the Poisson Pseudo-Maximum Likelihood (PPML) estimator of the gravity model on bilateral service exports data from Kenya to 176 countries, for the period 2005–2019, show that the effects of time zone differences between Kenya and partner countries is positive and statistically significant in technology-sensitive service exports (computer and information) while negative for construction and government service exports. Further analysis shows that these results are robust when an alternative model is employed and overlapping workday hours are used. The authors also find that the effect of time zone differences on services is nonlinear and sensitive to regulations and physical infrastructure (particularly mobile subscriptions). Attracting investment in technology-sensitive sectors should be encouraged through appropriate policy, given the positive impact of time zone differences on their exports. Traders in these sectors can also create networks with foreign firms. Deregulating and developing information and communication infrastructure, to expand mobile subscriptions, should also be encouraged.

Econometric Determinants of Chinese Developmental Finance in Sub-Saharan Africa; Further Evidence using a Flow-Type Decomposed Poisson Pseudo-Maximum Likelihood Model

Chinese “aid” has long engendered criticism. Western pundits and policymakers posit it as a political tool employed by Beijing to asway foreign policy concessions and secure natural resources access for its domestic industries, often atthe expense of the recipient country. However, we argue that large amounts of these claims lack empirical scrutiny or have been hindered by enduring conceptual, methodological, and data-centric constraints. This paper thus aims to refine and integrate prevailing methodological practices to produce a more nuanced understanding of Chinese motivations. Using empirical regression analysis and a newly released granular dataset spanning 48 Sub-Saharan African countries from 2000-2021, we: (1) decompose Chinese “aid” into flow types of relative concessionality; (2) utilize a Poisson pseudo-maximum likelihood (PPML) estimator to mitigate log-transformation and heteroskedasticity concerns present within traditional modeling of zero-inflated datasets; (3) retain a subset of contemporary values to deal with issues related to simultaneity in our regressors. Our findings suggest that while developmental goals primarily drive concessional aid, commercial lending is moreso influenced by economic self-interest, which is often incorrectly conflated with “aid” in the traditional sense. Further, Chinese “aid” does not flow disproportionately to corrupt or authoritarian regimes. This challenges the dominant “rogue donor” narrative and contributes to a more comprehensive perspective on China's emerging role in global developmental finance.

THE IMPACT OF DIGITAL SERVICES TRADE RESTRICTIVENESS ON TRADE IN TELECOMMUNICATIONS, COMPUTER, AND INFORMATION SERVICES: EVIDENCE FROM OECD COUNTRIES

This study analyzes the impact of digital services trade restrictiveness on trade in telecommunications, computer, and information services of Organisation for Economic and Co-operation Development countries by utilizing the Poisson Pseudo Maximum Likelihood method covering the period 2014-2022. The findings of the study statistically significantly confirm the disincentive impact of the higher degree of digital services trade restrictiveness on both exports and imports in telecommunications, computer, and information services. Therefore, more relaxing policies can most likely help to enhance the trade in this type of services due to mainly diminishing trade costs. Besides, to make use of more advantages of increasing digitalization, further cooperation and dialogue across countries, particularly with technologically advanced countries, is required. By this means, domestic services suppliers can attain foreign advanced knowledge and technology at relatively moderate costs, thus productivity can be improved, and eventually, more trade in services can be achieved.

Trade, Gravity, and Aggregation

Abstract Gravity equations are an important tool in empirical international trade research. We study to what extent sector-level parameters can be recovered from aggregate gravity equations estimated via Poisson pseudo maximum likelihood. We show that in the leading case where trade cost regressors do not vary at the sector level, estimates obtained with aggregate data have a clear interpretation as a weighted average of sectoral elasticities. Otherwise the estimates are biased, but researchers may possibly infer the direction of the bias. We illustrate our results by revisiting Baier and Bergstrand’s (2007) influential study of the effects of free trade agreements.

Do institutions matter for agri-food imports and exports between China and Africa? A gravity model analysis

This paper aims to study the role of institutional quality on agri-food trade (import and export) between China and 48 African countries during the 2001-2021 period. The gravity model of trade was employed by estimating the Generalised Least Square (GLS) and the Poisson Pseudo-Maximum Likelihood (PPML) estimators, which include zero trade flows for panel data. The main results show that voice and accountability, control of corruption, and the rule of law all enhance agri-food trade flows. While political instability encourages agri-food exports to China. In addition, the economic size of China, the trade cost (distance), and the population of African countries also encourage agri-food trade between China and African economies. Moreover, access to the sea, exchange rate policy, and the economic size of African nations deplete China’s agri-food imports from Africa. We showed the mechanism through which each institutional variable affects China’s agri-food trade flows to African nations.

Tác động của biến động tỷ giá hối đoái đến xuất khẩu nông nghiệp của Việt Nam và vai trò của tự do hóa tài chính tại nước đối tác

This study assesses the impact of real exchange rate volatility on Vietnam’s agricultural exports, considering the role financial liberalization in its trading partners. The author employs Poisson pseudomaximum likelihood estimators to estimate a gravity model covering bilateral agricultural exports from Vietnam to 187 its trading partners during 1996-2021. The empirical results of this study indicate that exchange rate volatility hampers agricultural exports of Vietnam and financial liberalization in its trading partners is crucial for alleviating this adverse nexus. Therefore, maintaining stable exchange rate is necessary to boost agricultural exports of Vietnam. In addition, under great turmoil in global economy with strong fluctuations in exchange rates, Vietnam still has a chance to increase its agricultural exports to countries that have high levels of financial liberalization. This finding has an important implication for selecting trading partners to improve export performance of agricultural sector in Vietnam.

Investigating the Validity of Climate Migration: Empirical Evidence from the Most Polluted Countries

The literature generally finds that lower air quality has been an important determinant of migration. This study builds a migration model employing annual data from 2010 to 2019 for the most polluted ten countries to test the validity of migration caused by air pollution through PM2.5 concentration. The Poisson Pseudo Maximum Likelihood method results show that air pollution is one of the most significant determinants of migration from the most polluted countries. Moreover, the low income level also pushes people to migrate more from their origin regions than richer ones. The study provides some policy recommendations for policy-makers in the countries where people breathe the most polluted air: (i) governments should follow growth-promoting economic policies; (ii) environment-friendly production techniques should be implemented to prevent worsening environmental quality; (iii) climate-induced mass migration should be considered while making security policy arrangements.

Impact of Anti-Dumping on Chinese Exports to Countries in ASEAN Plus 6

ABSTRACT Concerns about China’s excessive production capacity prompt a closer examination of Anti-dumping Duties (ADs) as a tool for managing trade imbalances. Within the ASEAN region, ASEAN plus 6 countries, especially India, are emerging as alternatives to China in global value chains. These countries import a broad range of products from China, including intermediate goods, making it vital to analyze the effects of ADs on these imports. Using the Poisson Pseudo-Maximum Likelihood (PPML) method, which effectively handles zero trade flows, heteroskedasticity, and endogeneity, this study explores the use of ADs beyond traditional major economies like the US and EU, focusing on their adoption by less economically developed countries. The findings show that ADs significantly curtail Chinese exports, potentially hindering stronger cooperation within ASEAN plus 6 and slowing regional trade dynamics. This research serves as a critical benchmark for assessing China’s strategic role in global economic leadership, viewed with reservations by several countries, including the US. It emphasizes the need to further explore China’s interaction with ASEAN plus 6 partner countries, particularly concerning trade remedy such as ADs and their impact on regional integration.

A gravity model analysis of trade regulations on wood products exports: Evidence from Cameroon, Ghana, and the republic of Congo

The study assesses the impact of the Forest Law Enforcement, Governance and Trade Voluntary Partnership Agreement (FLEGT VPA) and the Lacey Act Amendment (LAA) on the export quantities of wood products from Cameroon, Ghana and the Republic of Congo using the panel gravity Poisson Pseudo Maximum Likelihood (PPML) technique. The results indicate that FLEGT VPA had a negative and significant impact on industrial roundwood export quantity from all three countries. Similarly, its effects on the export of sawnwood and wood-based panels are also negative, except for Cameroon. On the other hand, the impact of LAA appears to be mixed. These results are validated by applying an alternative Driscoll-Kraay robust standard error estimation method.