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The purpose of this study is to account for a recent non-mainstream econometric approach using microdata and how it can inform research in business administration. More specifically, the paper draws from the applied microeconometric literature stances in favor of fitting Poisson regression with robust standard errors rather than the OLS linear regression of a log-transformed dependent variable. In addition, the authors point to the appropriate Stata coding and take into account the possibility of failing to check for the existence of the estimates – convergency issues – as well as being sensitive to numerical problems.

The author details the main issues with the log-linear model, drawing from the applied econometric literature in favor of estimating multiplicative models for non-count data. Then, he provides the Stata commands and illustrates the differences in the coefficient and standard errors between both OLS and Poisson models using the health expenditure dataset from the RAND Health Insurance Experiment (RHIE).

The results indicate that the use of Poisson pseudo maximum likelihood estimators yield better results that the log-linear model, as well as other alternative models, such as Tobit and two-part models.

The originality of this study lies in demonstrating an alternative microeconometric technique to deal with positive skewness of dependent variables.

The study performs an empirical test to assess the impact of the Pakistan-China Free trade agreement (FTA) on Pakistan, China, and the World's exports under homogenous and differentiated products. This study employs the modeling with Poisson specification with Poisson Pseudo-Maximum Likelihood method for the estimations. The results of empirical test show that the effect of FTA on the FTA and Non-FTA countries is greater in the differentiated product as compared to the homogenous product. Therefore, one of the most important policy implications provided by this study is that export enterprises need to concentrate on differentiated products as compare to the homogenous products after the implementation of the Pakistan-China FTA. Moreover, the previous literature concluded that Pakistan-China FTA was more beneficial for China as compared to Pakistan. However, according to this study, if Pakistani enterprises focus more on differentiated products as compared to homogenous products, then it will be equally beneficial for both Chinese and Pakistani enterprises. This study will contribute to the literature by considering the Bertrand competition between asymmetric countries and find out the effect of the FTA on these three countries. It considers China, Pakistan, and the Rest of the World as first, second, and third countries.

As a coastal emerging country, export-led marine economy has been the development model of Vietnam over the past decades since The Renovation 1986. Given the rise of globalization, regional economic integration and logistics enhancement have been identified as key engines for economic sustainability by Vietnamese government. Nevertheless, little sectoral and sub-sectoral evidence has been given for the platform shaped by policies relevant to export, logistics performance and regional economic integration. The paper employs the trade gravity model to study the relationship between seafood export, logistics performance and regional economic integration in the case of Vietnam. Sectoral and sub-sectoral trade gravity models are employed. Logistics performance from the exporter-side and importer-side is included in the estimations. Membership to effective regional trade agreements of Vietnam are proxies for regional economic integration. Zero trade issue is resolved by the Pooled Ordinary Least Squares (POLS), Poisson Pseudo-Maximum Likelihood (PPML) and Heckman Sample Selection estimations, while endogeneity is tackled by the difference and system Generalized Method of Moments (GMM) models. Findings vary by estimation methods, data levels, product groups, and whether which side is considered. In addition, theoretical contributions and some seafood export-driving policy recommendations relevant to regional economic integration and logistics performance development are discussed.

South Korea has signed and implemented 15 free trade agreements (FTAs) with 52 countries. More than 80 percent of imports of agricultural products came from FTA partner countries in 2015. We can say that South Korea entered the era of an opening in agricultural import sector. It means that FTA is an important factor in causing changes in agricultural imports. As a result of the implementation of the FTA, tariff cuts and other changes in trade conditions could lead to an increase in imports of agricultural products from FTA partner country or diversity of partners. South Korea has implemented 15 FTAs so far, each with a different period of implementation, different scale of trade, and different major trade items. This means that each FTA will have a different size and type of impact on the changes in the import structure. Therefore, the purpose of this paper is to analyze how the FTA actually affected agricultural imports and what type of impact each FTA had. Especially, the authors focused on the effects of trade creation and diversion to analyze the patterns of structural changes in the import of agricultural products according to the implementation of FTAs.

In this study, the authors analyzed both trade creation and trade diversion effect through the poisson pseudo-maximum likelihood method based on the previous research gravity model of Magee (2008, p. 353) and Yang and Martinez-Zarzoso (2014, p. 144). The biggest improvement compared to the standard gravity model is that all variables such as GDP, population, and distance are removed. This model cannot be regarded as a gravity model because the basic parameters of gravity model such as GDP, population, distance are excluded, but it can be said that the fixed effect variables replace the basic parameter of the gravity model.

According to the analysis, the authors found that the effects of trade creation were apparent in the early stages of FTA implementation before 2011 and the effect of the trade transition was seen in the mid-FTA transition period after 2011. The authors also clarified the pattern of structural changes in the agricultural imports of each FTAs. It is shown that the change in agricultural import structures was more apparent in major FTAs like the Korea-ASEAN, Korea-EU, and Korea-US FTA. In other words, the effects of trade creation and trade diversion in these FTAs were found to be statistically significant.

The limitations of this study are as follows. First, as multiple FTAs are implemented simultaneously, the effects of individual FTA can be offset. Second, the FTA effect of each item was not reflected, because it was analyzed based on the amount of imports by country. Third, the effect of the trade between the partners was not reflected. Therefore, future studies need to add or supplement these limitations.

This paper demonstrated through an empirical analysis that the FTA directly affects changes in agricultural import structure. And it proved that the period of FTA implementation, items imported from FTA partner countries, and the size of imports affected the structure of agricultural imports. Of course, changes in the domestic consumption patterns, changes in the supply and demand, conditions of quarantine inspection, and preference of importers are also factors that affect the structure of agricultural imports. It is expected that the effect of trade creation and the effect of trade diversion in agricultural import will be more significant when tariff rates are further decreased due to FTA implementation and domestic demand of agricultural product rises as a result of an economic recovery. As the FTA directly affects changes in agricultural imports, it should be carefully dealt with when signing a new FTA or improving the existing ones. And appropriate measures should be taken to minimize damages to the domestic agricultural sector due to changes in the import structure of agricultural products.

This paper fulfils an identified need to do research what kinds of effect occurred after FTA implementation in the agricultural sector. An empirical analysis was conducted on the effects of trade creation and diversion of agricultural products, based on the actual results of bilateral trade between the 50 major importers of agricultural products, including the 30 FTA partner countries.

The main aim of this paper is to verify whether the modern mainstream economic theory of multinational enterprise that explains foreign direct investment (FDI) from developed countries is also able to account for investment decisions of multinational enterprises (MNEs) from emerging economies.

Using Knowledge-And-Physical-Capital (KAPC) model as an analytical framework and Poisson-pseudo maximum likelihood estimation technique, the authors identify determinants of FDI flows from emerging economies. The data set consists of 38 home and 134 host countries during the period 2000–2012. Empirical evidence supports high explanatory power of KAPC model. Further, compared with the earlier Knowledge-Capital (KC) model, results confirm the importance of physical capital.

The estimation results confirm the hypothesis that mainstream economic theory can explain FDI flows from the emerging economies by highlighting the roles of total market size, skilled-labor abundance, investment and trade costs and geographical distance between two countries.

This study casts doubt on the alternative way that the KAPC model suggests to distinguish between horizontal and vertical FDI. The argument that horizontal MNE headquarters would be relatively more abundant than vertical MNE headquarters in countries that are abundant in physical capital relative to skilled labor seems reasonable but the idea of variable specification in the estimated equation should be revised.

Firms should be allowed to move their resources freely into and out of specific activities, both internally and internationally across border. To reach that goal, governments of potential host countries can adopt several measures, most importantly remove restrictions on payments, transfers and capital transactions and open previously closed industries to welcome foreign investment. In addition, to improve investment climate in general, governments need to pay attention to enhancing security of property rights, regulating internal taxation (i.e. corporate income tax), guaranteeing adequacy of infrastructure, efficient functioning of finance and labor markets and fighting against corruption.

The location choice of emerging investors set priority on similarity in economic size, geographical and cultural proximity. It is because shared borders or common official languages would reduce information costs and enhance information flows. Also, investors consider horizontal FDI (with motivation to expand market demand) as one of main modes of entry into a foreign market and a substitute for export. Likewise, distance is often understood as an important investment friction.

The outstanding contribution is that the research has uncovered the positive and statistically significant effect of physical capital on FDI activity, which has not been discussed in the earlier KC model. However, at the same time, the study casts doubt on the KAPC model's argument that relative abundance in physical capital to skilled labor between two countries determines FDI types and suggests that this argument and its empirical model specification should be carefully reviewed.

The purpose of this study is to investigate international trade determinants, paying special attention to variables related to climate change and non-tariff measures (NTMs), as they shape more and more world trade flows, with particular incidence on globalised goods, such as wine.

Based on panel data of Port wine exports to 60 countries, between 2006 and 2018, a gravity model has been estimated through Poisson pseudo-maximum likelihood. Explanatory variables include NTMs, mean temperature, temperature anomaly, gross domestic product (GDP), exchange rate, ad valorem equivalent tariffs and home bias.

The findings show that exports are inversely related to both mean temperature and temperature anomaly in importing countries. Regarding NTMs, it is found that only part of them are trade deterrent. Additionally, purchasing power in importing countries is one of the main determinants of Port wine exports.

The results show that, besides traditional economic variables, policymakers and wineries should include in their exports' decisions the impact of variables related to climate change and NTMs.

The novelty of this paper is to incorporate the impact of climatic variability of importing countries as a determinant of international trade of wine. Most former studies inspired of the gravity model consider explanatory variables such as GDP and exchange rate, and more recent ones started to consider NTMs too, however, this study may be the first paper to include the impact of climate change (quantified by mean temperature and temperature anomaly in importing countries) on exports.

The purpose of this paper is to analyze the impacts of differences in sanitary and phytosanitary measures as non-tariff measures (NTMs) in the tea trade between importing and exporting countries. With the progress of trade liberalization, there has been a shift of focus to NTMs as alternative or potential trade barriers.

In order to quantify an NTM on tea trade and implement its empirical application, this study designed an index of differences in maximum residue levels (MRLs) for the pesticide endosulfan and introduced it into a gravity trade model. The estimation challenges in the presence of heteroscedasticity and many zero-trade flows are resolved by taking the Heckman and Poisson pseudo-maximum likelihood estimators.

This study found that differences in MRLs, arising from the stricter standards in importing countries lead to a significant decrease in tea trade value. This negative impact of differences in MRLs is found to be slightly less than that of tariffs, implying that in this case, the NTM acts as a policy substitute for import tariffs in the global tea trade.

The main contribution of this study is to suggest and quantify the differences in MRLs across countries as a substantial NTM on the global tea trade and provide its empirical application.

The purpose of this paper is to identify trade integration and structure effects on bilateral trade between China and its partners, focusing on Chinese merchandise imports during the period 1995–2018.

The methodological approach applied here uses the augmented gravity model to investigate the factors lying behind import intensity, by use of the ordinary least squares (OLS) and Poisson pseudo maximum likelihood (PPML) estimators.

The findings provide evidence of complementarity between the Chinese demand and the world commodity markets. Free trade agreements between China and third countries seem to gradually lose significance, as the Chinese economy consolidates in world trade. Higher product diversification in export structures of China’s trading partners can become advantageous for facilitating market penetration. Diversification of energy resources, the steady, high demand for infrastructure equipment and more sophisticated consumer products constantly determine the structure of Chinese merchandise imports originating mainly and increasingly from countries with direct access to the Pacific Ocean.

The analytical breakdown of Chinese imports, presented in this paper, adds value to the existing literature with regard to trade structure analysis for China, paving the way for similar research for other developing countries as well.

The current study is designed to investigate the factors that foster the framing of destination competitiveness and establish the factors that drive the contribution of tourism innovations to economic growth in smart tourism destinations.

A four-year panel data were extracted from the World Economic Forum's travel and tourism competitiveness index and data were analysed using Poisson Pseudo Maximum Likelihood regression model.

The findings demonstrate that both the enabling environment and airport infrastructure significantly affect tourism's impact on the economy of the selected smart European tourism destinations. Conversely, human resources and general infrastructure display a negative correlation with tourism's contribution to the economy. However, no data in the sample support the idea that tourism policies, government prioritization or readiness of tourism information and communication technologies impact tourism's contribution to the economy. Additionally, the marginal effects indicate that improving the enabling environment and airport infrastructure can generate additional benefits for the economy through tourism.

The uniqueness of this study is the integration of smart tourism destinations with the measure of destination competitiveness to provide an empirical bridge that links tourism competitiveness to economic growth.

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.

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.

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.

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.