Job Market Paper

Abstract: How does international knowledge diffusion affect trade patterns, economic growth and welfare across the globe? This paper tackles this question by estimating a novel dynamic trade model where heterogeneous firms innovate. To motivate the analysis, I document stylized facts about international knowledge diffusion and technology adoption using comprehensive Chinese firm-level data on trade, patents and citations. To account for these patterns, I develop a dynamic general equilibrium model where firms learn from sellers when importing and choose to adopt foreign technologies when exporting. Firms’ sales and entry decisions in response to a trade cost reduction differ depending on the knowledge gap between the domestic and foreign countries. I structurally estimate the model with bilateral trade flows for the global economy. I find that knowledge diffusion substantially increases the gains from trade in all economies, ranging from 0.2% to 8.7%. However, foreign technology adoption can reduce welfare in knowledge-abundant countries as their technological advantage gets eroded. Technology adoption therefore alters the conventional gains from trade, with developed countries potentially benefiting from higher trade barriers.  


Matlab code 

Abstract: This paper argues that the lockdown of Hubei province in China due to the Coronavirus outbreak provides a natural experiment to study the importance of China’s role in global value chains. Since the lockdown started during the Lunar New Year, Hubei’s migrant workers who went home could not return to workplaces in other provinces, resulting in a massive labor supply shock. I feed the supply shock through a Ricardian model with intermediate goods and sectoral linkages to study trade and welfare effects across several economies. While welfare in China is the most negatively affected, the shock also has sizeable negative implications for the US and the UK.

Other working papers

[funded by STEG PhD grant 1286] 

Abstract: A standard structural change model with intra-household bargaining, connecting Ngai and Petrongolo (2017) and Blundell et al. (2005), predicts that moving out of agriculture increases the female bargaining position by an increase in female-to-male wage ratio due to the rising service sector. However, we reject this prediction using rich micro-level data from Sub-Saharan Africa with both two-way fixed effects estimation and instrumental variable approach. Structural transformation has significantly widened the gender employment gap in SSA. To reconcile this fact, we build a two-sector general equilibrium model with social stigma against women working in the service sector to show that structural transformation can reduce female bargaining power if the social stigma is larger than a threshold jointly determined by female comparative advantage and substitutability of labor input between genders. We emphasize that structural transformation may be insufficient for gender equality; active policies are needed to ensure equal gender access to service sector jobs.

Abstract: This paper proposes a new method of estimating non-stationary nonlinear dynamic general equilibrium models, with an application in the structural transformation context. By combining different sectoral growth rates with different factor intensities, I construct a three-sector general equilibrium model that generates a hump-shaped path for the size of the manufacturing sector while replicating the observed pattern of increasing and decreasing shares in services and agriculture. Using data for the United States and Sweden over the past decades, I implement a relaxation algorithm to solve the model for non-stationary paths of sectoral shares for given parameter values and then estimate the best fit for the model’s parameters. A counterfactual exercise for China shows the importance of trade in explaining structural change. This method can be easily generalized to solve similar problems in different contexts.

Publications before PhD

Abstract: Since China's opening up and reform began in the late 1970s, China's economy has taken off with a rapid increase in energy consumption. However, due to the significant differences in economic and social development across regions, the patterns and characteristics of energy consumption in different Chinese provinces vary remarkably. In this study, the relationship between energy consumption per capita and GDP per capita is examined for all of the 30 individual Chinese provinces. To address the possible non-stationary time series for individual provinces, the autoregressive distributed lag (ARDL) modelling approach is utilized. The estimation results indicate that the relationships between energy consumption per capita and GDP per capita are quite different across provinces. Although, for most provinces, the relationship is linear and no turning point of energy consumption per capita is detected, for some provinces, the relationship is estimated to be inverted-U or inverted-N shaped, suggesting the existence of the peak of energy consumption per capita in these provinces. Furthermore, it is also found that the secondary industry plays an important role in energy consumption per capita. 

Abstract: With rapid economic development, the Chinese government expenditures at various levels have increased sufficiently. At the same time, the environmental pollution in China has deteriorated significantly. In this study, the city-level panel data of 106 Chinese cities over the 2002–2014 period are utilized to investigate the impacts of government expenditure on the emissions of three typical pollutants. Specifically, the total effects are divided into two types: direct effects, through which government expenditure affects pollution directly; and indirect effects, which refer to the indirect influences of government expenditure on environmental pollution through its impacts on GDP per capita. To control for potential endogeneity and introduce dynamics, the generalized method of moments (GMM) method is utilized. The estimation results indicate that the total effects of government expenditure on these three pollutants are very different: for sulfur dioxide (SO2), soot and chemical oxygen demand (COD), the total effects are decreasing, inverted-U and U-shaped, respectively. Furthermore, the indirect effects dominate the direct effects.

Abstract: As the main greenhouse gas, carbon dioxide (CO2) has been under intensive study in the last two decades. This paper addresses the research that whether the environmental Kuznets curve (EKC) for CO2 emissions exists in the G20 group—an international forum for governments and central banks from 19 countries and European Union. To analyze the studied relationship thoroughly, other four explanatory variables—two trade openness terms, the ratio of secondary industry value-added to GDP and population density—are employed to investigate whether they have any influences on the existence and shapes of EKC. In the empirical study, two multinational panel data sets covering the periods between 1960 and 2010 (50 years) and between 1990 and 2010 (20 years) are utilized, and the panel data fixed effects and generalized method of moments estimators are employed. The estimation results indicate that the EKC indeed exists in the G20 members as a whole. To investigate whether the existence of EKC depends on the level of economic growth, the G20 countries are further divided into two subgroups: developed and developing countries. Although the estimation results suggest that there exists EKC in developing countries during both 20- and 50-year periods, there is no persuasive evidence to prove the existence of EKC in developed countries during the 20-year period. For the time periods we studied, most developed countries have seen relatively stable or even decreasing CO2 emissions, while for the majority of the developing countries, the peak of CO2 emissions could not be reached in the near future. 

Abstract: During the last two decades of China's rapid economic growth, the gap in citizens’ income has widened and environmental quality has deteriorated. Using Gini coefficients as the measure of income inequality, this study investigated the impacts of income inequality on carbon emissions per capita in China. To control for potential endogeneity and allow for dynamics, the Generalized Method of Moments (GMM) technique is utilized. Moreover, the influential factors that can affect carbon emissions per capita in China have been examined. The empirical results indicate that carbon emissions per capita increase as the income gap expands for nationwide and in the eastern and non-eastern regions of China. Among all factors that may affect carbon emissions per capita, a “U” shaped relationship exists between per capita income and per capita carbon emissions, and increasing the value-added share of secondary industry in the GDP would significantly increase carbon emissions per capita.

Abstract: As China's economy has grown rapidly in recent years, China's environmental pollution has become increasingly significant. Among all the traditional pollutants, sulfur dioxide has been monitored by the Chinese government since the 1990s. In this study, China's city-level panel data between 2002 and 2012 are utilized to investigate the existence of convergence in per capita sulfur dioxide emissions across Chinese cities. The conventional estimation methods for β-convergence suffer from an endogeneity problem and therefore produce biased results. To address the endogeneity problem and allow for dynamics, dynamic panel data estimators are utilized, and the static estimation results are conducted as a robustness check. In addition, the influential factors for convergence are examined. The empirical results indicate that, in the chosen sample period, there were absolute and conditional convergences in per capita sulfur dioxide emissions across cities within the whole nation as well as in the eastern, western and central regions of China. Because per capita Gross Domestic Product and the ratio of secondary industry to Gross Domestic Product are both positively related with per capita sulfur dioxide emissions, higher income per capita and the greater importance of the secondary industry would cause the convergence speed to be lower. Therefore, the most straightforward policy implication for the empirical results is that the policies for controlling sulfur dioxide emissions should be regionally differentiated: for cities with high sulfur dioxide emissions per capita, the regulation could be tight, as the emissions would decrease faster because convergence exists; however, for cities with low sulfur dioxide emissions per capita, the target for reducing emissions should not be excessively aggressive. 

Work in progress

Abstract: While the literature on social media adoption in marketing is growing, a dearth of research specifically examines the impact of social media adoption on small and medium-sized enterprises (SMEs). To address this gap, this study focuses on fast-food SMEs in Pakistan and investigates the impact of Facebook and Instagram adoption on their marketing performance. We adopt a multiple case study approach using the technology-organisation-environment (TOE) framework with the empirical data collected from twenty-seven SMEs. Our study offers a refined conceptual framework that highlights the importance of complexity, compatibility, innovativeness, and government support as critical factors that influence the adoption of Facebook and Instagram for marketing by fast-food SMEs. Our findings indicate that adopting social media platforms can improve customer relations and help SMEs reach their target audience.