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Culture and institutions are among the essential sources of comparative advantage in international trade and may influence a country's FDI influx. This paper aims to…
Culture and institutions are among the essential sources of comparative advantage in international trade and may influence a country's FDI influx. This paper aims to analyze the impact of cultural distance (CD) and institutional distance (ID) on the efficiency of China's outward foreign direct investment (OFDI) for the panel of 43 countries during 2003–2016.
The stochastic frontier approach (SFA) has been incorporated into the standard gravity model of gravity Kalirajan, 1999; Ravishankar and Stack, 2014). SFA has traditionally been implemented to evaluate the production frontier as the highest yield that could possibly be generated from specified input levels. The production process is viewed to be fully efficient if the real output is performed at frontier level. Otherwise, the production process is assumed technically inefficient, which implies potential scope for enhanced output. This error term is split into two parts, a non-negative term and more standard asymmetrical term. The former identifies inefficiencies in production, while the latter retrieves random disorders
The outcomes assert a U-shaped relationship between CD and the efficiency of China's OFDI. Put differently, when the CD is minimal, the “liability of foreignness” (LOF) effect plays a dominant role; and CD tends to reduce the efficiency of China's OFDI. On the flip side, when the culture distance is greater than a certain threshold level, the “advantages of foreignness” (AOF) effect plays a predominant role, and CD improves the efficiency of China's OFDI. Institutional distance results in the “LOF” effect significantly reduce the efficiency of China's OFDI.
Notwithstanding these contributions, our study has some limitations which offer directions for future research. The major limitation of this research work is the availability of comprehensive data for a well extended time, in particular for the variable of CD. Further, a firm-level study can shed light on the motivations and performance of China OFDI. Finally, given that our analysis focuses on emerging market multinational enterprises (EMNEs) from China, the findings might not be explicitly generalizable to MNEs from other developing countries. Future studies should concentrate on the comparative study of China's OFDI with other developing countries, to deepen our understanding of the effects of ID and CD on the efficiency of OFDI.
(1) The work is novel in nature as the authors attempt to explore the effect of ID and CD on efficiency of Chinese FDI. To the best of the authors’ knowledge, no research is conducted in this direction in terms of Chinese FDI. (2) Further, the prior studies employed standard gravity model, which may not correctly evaluate the trade potential viewed as the highest potential value. To overcome the shortcomings of the standard gravity model in estimation of the trade performance and efficiency, the SFA has been incorporated into the standard gravity model of gravity.
The objective of this paper is threefold. First, it aims to empirically study whether firm-specific/idiosyncratic uncertainty, macroeconomic/aggregate uncertainty and…
The objective of this paper is threefold. First, it aims to empirically study whether firm-specific/idiosyncratic uncertainty, macroeconomic/aggregate uncertainty and political uncertainty have an adverse influence on firms' investment decisions in Pakistan. After establishing this, it scrutinizes whether the uncertainty effects on investment are different for firms of different sizes. Finally, it investigates whether any heterogeneity exists in the uncertainty impacts across different industries.
The empirical analysis is based on an unbalanced panel data of 468 nonfinancial firms listed at the Pakistan Stock Exchange (PSX) during the period 2000–2018. Departing from the literature, the paper builds a time-varying composite volatility/uncertainty index based on the principal component analysis (PCA) by utilizing the constructed volatility series for sales, cash flows and return on assets to gauge firm-specific uncertainty for each firm included in the analysis. Likewise, the paper develops a PCA-based composite index for macroeconomic uncertainty by using the conditional variance series of consumer price index (CPI), industrial production index (IPI), the interest rate and the exchange rate obtained by estimating the (generalized) autoregressive conditional heteroscedastic, (G)ARCH, models. Finally, political uncertainty is measured by political risk components maintained by the Political Risk Services Group. The empirical framework of the paper augments the standard investment equation by incorporating all three types of uncertainty. Firms are grouped into small, medium and large categories based on firms' total assets and the size indicators are generated. Next, the indicators are multiplied by each uncertainty measure to quantify the differential effects of uncertainty across firm size. Firms are also differentiated by sectors to explore the sector-based asymmetries in the uncertainty effects. The “robust two-step system generalized method of moments (2SYS GMM) (dynamic panel data) estimator” is applied to estimate the empirical models.
The results provide robust and strong evidence of the detrimental influence of all three types of uncertainty on investment. Yet, it is observed that the strength of the influence considerably varies across uncertainty types. In particular, compared to firm-specific uncertainty, both macroeconomic and political uncertainties have more unfavorable effects. The analysis also reveals that the effects of all three types of uncertainty are quite different at small, medium and large firms. Specifically, it is observed that although the investment of all firms is influenced adversely by magnified uncertainty, the adverse effects of all three kinds of uncertainty are quite stronger at small firms than medium and large firms. These findings support the phenomenon of size-based asymmetries in the effects of uncertainty on investment. The results also provide evidence that either type of uncertainty quite differently affects the investment policy of firms in different sectors.
The findings help different stakeholders to know how different types of uncertainty differently affect corporate firms' investments. Further, they suggest that firm size has a vital role in ascertaining the adverse effects of uncertainty on investment. The paper identifies to which type of uncertainty investors and policymakers should care more about and to which types of firms and industries they should concern more during volatile times. Firms should have more fixed assets and expand their size to mitigate the detrimental effects on investment of internal and external uncertainties. The government should enhance the political stability to induce firms for a higher level of investment, which, in turn, will result in higher growth of the economy.
The originality of the paper is credited to four aspects. First, unlike most previous studies that have utilized a single volatility measure, this paper constructs composite uncertainty indices based on the weights determined by the PCA. Second, it examines the effect of political uncertainty over and above the effects of idiosyncratic and aggregate (macroeconomic uncertainty) for an emerging economy. Third, and most important, it provides first-hand empirical evidence on the role of firm size in establishing the asymmetric effects of uncertainty on investment. Finally, it provides evidence on the industry-based heterogeneity in the uncertainty effects.
Convection is one of the main heat transfer mechanisms in both high to low temperature media. The accurate convection heat transfer coefficient (HTC) value is required for…
Convection is one of the main heat transfer mechanisms in both high to low temperature media. The accurate convection heat transfer coefficient (HTC) value is required for exact prediction of heat transfer. As convection HTC depends on many variables including fluid properties, flow hydrodynamics, surface geometry and operating and boundary conditions, among others, its accurate estimation is often too hard. Homogeneous dispersion of nanoparticles in a base fluid (nanofluids) that found high popularities during the past two decades has also increased the level of this complexity. Therefore, this study aims to show the application of least-square support vector machines (LS-SVM) for prediction of convection heat transfer coefficient of nanofluids through circular pipes as an accurate alternative way and draw a clear path for future researches in the field.
The proposed LS-SVM model is developed using a relatively huge databank, including 253 experimental data sets. The predictive performance of this intelligent approach is validated using both experimental data and empirical correlations in the literature.
The results show that the LS-SVM paradigm with a radial basis kernel outperforms all other considered approaches. It presents an absolute average relative deviation of 2.47% and the regression coefficient (R2) of 0.99935 for the estimation of the experimental databank. The proposed smart paradigm expedites the procedure of estimation of convection HTC of nanofluid flow inside circular pipes.
Therefore, the focus of the current study is concentrated on the estimation of convection HTC of nanofluid flow through circular pipes using the LS-SVM. Indeed, this estimation is done using operating conditions and some simply measured characteristics of nanoparticle, base fluid and nanofluid.