Trust, Efficient Contracting and Export Upgrading

Informal contracting institutions constitute an essential part of a country’s overall contracting institution, however, the nascent literature examining the effect of contracting institutions on the quality of products a country produces and exports, have paid a limited attention on the role of informal contracting institutions. We fill this gap in the literature by examining whether higher trust levels, as an informal contracting institution, leads to product-quality upgrading by reducing contractual frictions and opportunistic behaviors. Using industry-level data spanning 1995–2014, we examined this relationship using the generalized difference-in-difference method. We find that contract-intensive industries in trust-intensive societies experience a disproportionally higher increase in the production and export of higher-quality products compared to those industries in low-trusting societies. This result holds after controlling for conventional sources of comparative advantage and formal contracting institution. Hence, the result underscores the importance of informal contracting institutions for improved economic performance and stress the crucial fact that countries with strong and efficient informal institutions can still benefit in market-related activities even in the presence of weak formal institutions.

IS THERE J-CURVE EFFECT IN THE TRADE BETWEEN PAKISTAN AND UNITED KINGDOM? ASYMMETRIC EVIDENCE FROM INDUSTRY LEVEL DATA

Pakistan is a country which is facing chronic trade deficit since its independence and currency devaluation have always remained an effective strategy to bridge this gap between imports and exports. Previous studies which assessed the influence of changes in exchange rate on Pakistan’s trade balance followed a symmetric or linear approach. However, in this study we adopt an asymmetric approach, according to which appreciations and depreciations have asymmetric effects on the trade balance of Pakistan. Using commodity trade data of 28 (2-digits) industries that trade between Pakistan and United Kingdom, we find pattern of the J-curve in nine industries when a linear model was estimated. However, when we estimated a nonlinear model, the concept of asymmetric J-curve was supported in 14 industries. The largest industry (clothing) which engages in 36.5% of the trade was found to benefit from rupee depreciation.

Sectoral risk assessment: a case of the Latvian forestry sector

The present study provides an analysis of sectoral risk in the forestry sector and presents an overview of multiple-criteria decision analysis (MCDA) for sector development assessment. The main aim of the paper is to determine the macroeconomic indicators and to assess sectorial risk, which is caused by unexpected macroeconomic and market changes. The paper presents a methodological framework for the analysis of sectoral level risk to assess the probability of the stable development of the industry and to determine the risk for the forestry sector (industry). Based on expert opinions and analytic hierarchy process (AHP), the authors have identified and evaluated macroeconomic industry-level data indicators (factors) used to determine the development of the forestry sector. An analysis matrix with the defined and verified indicators (factors) is presented; the comparison between sectoral inicators and sectoral volatility is shown. In order to combine industry development indicators (factors) expressed in different units of meas-urement and to establish a comprehensive indicator of industry development, the statistical standardisation (normalisation) of indicators is performed.

Unpacking Skill Bias: Automation and New Tasks

We extend the canonical model of skill-biased technical change by modeling the allocation of tasks to factors and allowing for automation and the creation of new tasks. In our model, factor prices depend on the set of tasks they perform. Automation can reduce real wages and generate sizable changes in inequality associated with small productivity gains. New tasks can increase or reduce inequality depending on whether they are performed by skilled or unskilled workers. Industry-level data suggest that automation significantly contributed to the rising skill premium, while new tasks reduced inequality in the past but have contributed to inequality recently.

Nowhere to Go: FDI, Terror, and Market-specific Assets

Under what circumstances does terrorism repel foreign investment? The negative effect of terrorism on foreign investment identified in current scholarship masks heterogeneity across host markets and industries. Foreign investment ought to react less to political violence when host markets match firms’ input requirements, when firms lack viable alternative hosts, and when assets are immobile across markets. We model the endogenous codetermination of terror and investment to derive these comparative statics, highlighting empirical challenges in identifying the effects of terror on foreign direct investment. To overcome these obstacles, we use an instrumental variable estimator which exploits differences in the networks along which terror and investment spread. Using industry-level data on the activities of US multinationals, we test our model and conclude that foreign investors that find it hard to leave particular host markets are doubly penalized: their lack of outside options makes them tempting targets for terror. Our findings have implications for other forms of violent and nonviolent political tactics which affect multinationals and for understanding how foreign investment reacts to heightened risk in host markets.