Another Look at what to do with Time-series Cross-section Data

Our study revisits Beck and Katz' (1995) comparison of the Parks and PCSE estimators using time-series, cross-sectional data (TSCS). Our innovation is that we construct simulated statistical environments that are designed to approximate actual TSCS data. We pattern our statistical environments after income and tax data on U.S. states from 1960-1999. While PCSE generally does a better job than Parks in estimating standard errors/confidence intervals, it too can be unreliable, sometimes producing standard errors/confidence intervals that are substantially off the mark. Further, we find that the benefits of PCSE can come at a large cost in estimator efficiency.Panel data, Parks model; PCSE estimator; Monte Carlo methods

A Monte Carlo Evaluation of the Efficiency of the PCSE Estimator

Panel data characterized by groupwise heteroscedasticity, cross-sectional correlation, and AR(1) serial correlation pose problems for econometric analyses. It is well known that the asymptotically efficient, FGLS estimator (Parks) sometimes performs poorly in finite samples. In a widely cited paper, Beck and Katz (1995) claim that their estimator (PCSE) is able to produce more accurate coefficient standard errors without any loss in efficiency in ¡°practical research situations.¡± This study disputes that claim. We find that the PCSE estimator is usually less efficient than Parks -- and substantially so -- except when the number of time periods is close to the number of cross-sections.Panel data estimation; Monte Carlo analysis; FGLS; Parks; PCSE; finite sample

Another Look At What To Do With Time-Series Cross-Section Data

Our study revisits Beck and Katz’ (1995) comparison of the Parks and PCSE estimators using time-series, cross-sectional data (TSCS). Our innovation is that we construct simulated statistical environments that are designed to closely match “real-world,” TSCS data. We pattern our statistical environments after income and tax data on U.S. states from 1960-1999. While PCSE generally does a better job than Parks in estimating standard errors, it too can be unreliable, sometimes producing standard errors that are substantially off the mark. Further, we find that the benefits of PCSE can come at a substantial cost in estimator efficiency. Based on our study, we would give the following advice to researchers using TSCS data: Given a choice between Parks and PCSE, we recommend that researchers use PCSE for hypothesis testing, and Parks if their primary interest is accurate coefficient estimates.Panel Data, Panel Corrected Standard Errors, Monte Carlo analysis

Two essays on international economics.

Developing countries in the past three decades embraced capital account liberalization as a way of attracting international capital flows in hope of boosting economic growth. But the outcomes of the policy across countries are contingent on the initial economic conditions, the pace of trade liberalization, and the features of other domestic structural reforms. The second chapter directly examines the rarely discussed optimal liberalization sequence among different capital account transactions and extends the literature on the subject along two dimensions. First, I create liberalization intensity indicators for three types of capital transactions: banking transactions, portfolio investment transactions, and direct investment transactions based on the IMF disaggregated restriction dummies for 12 subcategories of capital transactions in a sample of 33 countries, most of them OECD countries. Second, in a multiplicative interaction model, I find the optimal sequence of liberalizing portfolio investment transactions 5 years earlier and direct investment transactions 1 year earlier than banking transactions is correlated with 0.6 percent higher annual economic growth rate in the 1990s.The first chapter proposes three hypotheses about the effects of government stability and encompassing interest, which originated from Olson (1982) classic, The Rise and Decline of Nations, on cross-country economic growth. First, the government stability affects the average economic growth rate concavely. Second, encompassing interest has a convex effect on expected growth rate. Third, two nonlinear effects integrate into a polynomial W-shaped curve. The hypotheses are tested on two datasets: Cross National Time Series (1975) and World Handbook of Political and Social Indicators III (1986). A wide variety of government stability and encompassing interest measures provide solid statistical evidence for the two nonlinear effects as well as the polynomial effect

Does Management’s Attention to Different Facets of Entrepreneurial Orientation Create Value for the Firm? A Longitudinal Study of Large Retailers

Studies of entrepreneurial orientation tend to merge its three components—proactiveness, risk-taking, and innovativeness—into a monolithic construct and analyze its relationship with firm outcomes at one point in time. This has resulted in knowledge voids related to the relative importance of the different components, their specific effect on value created by the firm, and their evolution over time. The present study links each component of entrepreneurial orientation to economic value creation using a longitudinal dataset. Results provide support for hypothesized relationships. Implications and avenues for future research are discussed

Estimating the economic impact of large hydropower projects: a dynamic multi-regional computable general equilibrium analysis

In response to rapidly growing energy demands, Chinese authorities plan to invest more in hydropower development. However, there are concerns about the possible effects on macroeconomy. This paper uses SinoTERM, a dynamic multi-regional computable general equilibrium model (CGE) of the Chinese economy, to analyze the economic impact of large hydropower development projects. The model features regional labor market dynamics and an electricity subdivision module with substitutability between various types of electricity generation. The results suggest that hydropower development will boost economic growth in the project region. Most sectors in the project region will benefit from the hydropower development such as other services, health, and education, while some sectors will suffer a loss in output because of the substantial increase in real wages. For the national, every 10,000 yuan investment can drive the national GDP growth of 1,000 yuan, and the cost is expected to be recovered in ten years. By the end of 2040, the real national wage will be around 0.16% higher than the baseline scenario. The project could only be justified if net environmental benefits outweigh this loss

Probing the active sites of site-specific nitrogen doping in metal-free graphdiyne for electrochemical oxygen reduction reactions

Abstract(#br)The development of highly active and low-cost catalysts for electrochemical reactions is one of the most attractive topics in the renewable energy technology. Herein, the site-specific nitrogen doping of graphdiyne (GDY) including grap-N, sp-N(I) and sp-N(II) GDY is systematically investigated as metal-free oxygen reduction electrocatalysts via density functional theory (DFT). Our results indicate that the doped nitrogen atom can significantly improve the oxygen (O 2 ) adsorption activity of GDY through activating its neighboring carbon atoms. The free-energy landscape is employed to describe the electrochemical oxygen reduction reaction (ORR) in both O 2 dissociation and association mechanisms. It is revealed that the association mechanism can provide higher ORR onset potential than dissociation mechanism on most of the substrates. Especially, sp-N(II) GDY exhibits the highest ORR electrocatalytic activity through increasing the theoretical onset potential to 0.76 V. This work provides an atomic-level insight for the electrochemical ORR mechanism on metal-free N-doped GDY

Diagnostic performance of IVUS-FFR analysis based on generative adversarial network and bifurcation fractal law for assessing myocardial ischemia

BackgroundIVUS-based virtual FFR (IVUS-FFR) can provide additional functional assessment information to IVUS imaging for the diagnosis of coronary stenosis. IVUS image segmentation and side branch blood flow can affect the accuracy of virtual FFR. The purpose of this study was to evaluate the diagnostic performance of an IVUS-FFR analysis based on generative adversarial networks and bifurcation fractal law, using invasive FFR as a reference.MethodIn this study, a total of 108 vessels were retrospectively collected from 87 patients who underwent IVUS and invasive FFR. IVUS-FFR was performed by analysts who were blinded to invasive FFR. We evaluated the diagnostic performance and computation time of IVUS-FFR, and compared it with that of the FFR-branch (considering side branch blood flow by manually extending the side branch from the bifurcation ostia). We also compared the effects of three bifurcation fractal laws on the accuracy of IVUS-FFR.ResultThe diagnostic accuracy, sensitivity, and specificity for IVUS-FFR to identify invasive FFR≤0.80 were 90.7% (95% CI, 83.6–95.5), 89.7% (95% CI, 78.8–96.1), 92.0% (95% CI, 80.8–97.8), respectively. A good correlation and agreement between IVUS-FFR and invasive FFR were observed. And the average computation time of IVUS-FFR was shorter than that of FFR-branch. In addition to this, we also observe that the HK model is the most accurate among the three bifurcation fractal laws.ConclusionOur proposed IVUS-FFR analysis correlates and agrees well with invasive FFR and shows good diagnostic performance. Compared with FFR-branch, IVUS-FFR has the same level of diagnostic performance with significantly lower computation time