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Journal articles on the topic 'Panel data regressions'

Author: Grafiati

Published: 11 September 2021

Last updated: 30 July 2025

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1

Hjalmarsson, Erik. "Predictive Regressions with Panel Data." International Finance Discussion Paper 2006, no. 869 (2006): 1–39. http://dx.doi.org/10.17016/ifdp.2006.869.

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2

Arellano, Manuel, and Stéphane Bonhomme. "Nonlinear panel data estimation via quantile regressions." Econometrics Journal 19, no. 3 (2016): C61—C94. http://dx.doi.org/10.1111/ectj.12062.

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3

Cheng, Jing, and Mingyao Ai. "Optimal designs for panel data linear regressions." Statistics & Probability Letters 163 (August 2020): 108769. http://dx.doi.org/10.1016/j.spl.2020.108769.

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4

Moon, Hyungsik Roger, and Benoit Perron. "PETER C.B. PHILLIPS’S CONTRIBUTIONS TO PANEL DATA METHODS." Econometric Theory 30, no. 4 (2014): 882–93. http://dx.doi.org/10.1017/s0266466613000509.

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This paper discusses Peter Phillips’s contributions to panel data methods. These include contributions in the areas of seemingly unrelated regressions, nonstationary panel data, dynamic panels, and the development of multiple index asymptotic theory. We also discuss his empirical contributions in the area of economic growth and convergence that use macro panel data.

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Baltagi, Badi H., and Ping X. Wu. "UNEQUALLY SPACED PANEL DATA REGRESSIONS WITH AR(1) DISTURBANCES." Econometric Theory 15, no. 6 (1999): 814–23. http://dx.doi.org/10.1017/s0266466699156020.

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This paper deals with the estimation of unequally spaced panel data regression models with AR(1) remainder disturbances. A feasible generalized least squares (GLS) procedure is proposed as a weighted least squares that can handle a wide range of unequally spaced panel data patterns. This procedure is simple to compute and provides natural estimates of the serial correlation and variance components parameters. The paper also provides a locally best invariant test for zero first-order serial correlation against positive or negative serial correlation in case of unequally spaced panel data.

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Baltagi. "Specification Tests in Panel Data Models Using Artificial Regressions." Annales d'Économie et de Statistique, no. 55/56 (1999): 277. http://dx.doi.org/10.2307/20076199.

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7

Belhadj, Besma. "Fuzzy multiple regressions for Cross-Section and Panel data." Socio-Economic Planning Sciences 91 (February 2024): 101761. http://dx.doi.org/10.1016/j.seps.2023.101761.

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8

Allison, Paul D. "Asymmetric Fixed-effects Models for Panel Data." Socius: Sociological Research for a Dynamic World 5 (January 2019): 237802311982644. http://dx.doi.org/10.1177/2378023119826441.

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Standard fixed-effects methods presume that effects of variables are symmetric: The effect of increasing a variable is the same as the effect of decreasing that variable but in the opposite direction. This is implausible for many social phenomena. York and Light showed how to estimate asymmetric models by estimating first-difference regressions in which the difference scores for the predictors are decomposed into positive and negative changes. In this article, I show that there are several aspects of their method that need improvement. I also develop a data-generating model that justifies the

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Karnik, Ajit, and Mala Lalvani. "Heterogeneity in Growth Processes: Estimating Growth Regressions using Panel Data." International Economic Journal 23, no. 4 (2009): 561–90. http://dx.doi.org/10.1080/10168730903372224.

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10

Jochmans, Koen, and Martin Weidner. "Fixed‐Effect Regressions on Network Data." Econometrica 87, no. 5 (2019): 1543–60. http://dx.doi.org/10.3982/ecta14605.

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This paper considers inference on fixed effects in a linear regression model estimated from network data. An important special case of our setup is the two‐way regression model. This is a workhorse technique in the analysis of matched data sets, such as employer–employee or student–teacher panel data. We formalize how the structure of the network affects the accuracy with which the fixed effects can be estimated. This allows us to derive sufficient conditions on the network for consistent estimation and asymptotically valid inference to be possible. Estimation of moments is also considered. We

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11

Barros, Lucas, F. Henrique Castro, Alexandre da Silveira, and Daniel Bergmann. "Endogeneity in panel data regressions: methodological guidance for corporate finance researchers." Review of Business Management 22, Special Issue (2020): 437–61. http://dx.doi.org/10.7819/rbgn.v22i0.4059.

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12

International Monetary Fund. "Oil Rents, Corruption, and State Stability: Evidence From Panel Data Regressions." IMF Working Papers 09, no. 267 (2009): 1. http://dx.doi.org/10.5089/9781451874129.001.

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13

Arezki, Rabah, and Markus Brückner. "Oil rents, corruption, and state stability: Evidence from panel data regressions." European Economic Review 55, no. 7 (2011): 955–63. http://dx.doi.org/10.1016/j.euroecorev.2011.03.004.

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14

Moody, Carlisle E., and Thomas B. Marvell. "Clustering and Standard Error Bias in Fixed Effects Panel Data Regressions." Journal of Quantitative Criminology 36, no. 2 (2018): 347–69. http://dx.doi.org/10.1007/s10940-018-9383-z.

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15

Oberfichtner, Michael, and Harald Tauchmann. "Stacked linear regression analysis to facilitate testing of hypotheses across OLS regressions." Stata Journal: Promoting communications on statistics and Stata 21, no. 2 (2021): 411–29. http://dx.doi.org/10.1177/1536867x211025801.

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In empirical work, researchers frequently test hypotheses of parallel form in several regressions, which raises concerns about multiple testing. One way to address the multiple-testing issue is to jointly test the hypotheses (for example, Pei, Pischke, and Schwandt [2019, Journal of Business & Economic Statistics 37: 205–216] and Lee and Lemieux [2010, Journal of Economic Literature 48: 281–355]). While the existing commands suest (Weesie, 1999, Stata Technical Bulletin Reprints 9: 231–248) and mvreg enable Stata users to follow this approach, both are limited in several dimensions. For in

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16

Blackwell, J. Lloyd. "Estimation and Testing of Fixed-effect Panel-data Systems." Stata Journal: Promoting communications on statistics and Stata 5, no. 2 (2005): 202–7. http://dx.doi.org/10.1177/1536867x0500500205.

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This paper describes how to specify, estimate, and test multiple-equation, fixed-effect, panel-data equations in Stata. By specifying the system of equations as seemingly unrelated regressions, Stata panel-data procedures worked seamlessly for estimation and testing of individual variable coefficients, but additional routines using test were needed for testing of individual equations and differences between equations.

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17

Canitz, Felix, Panagiotis Ballis-Papanastasiou, Christian Fieberg, Kerstin Lopatta, Armin Varmaz, and Thomas Walker. "Estimates and inferences in accounting panel data sets: comparing approaches." Journal of Risk Finance 18, no. 3 (2017): 268–83. http://dx.doi.org/10.1108/jrf-11-2016-0145.

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Purpose The purpose of this paper is to review and evaluate the methods commonly used in accounting literature to correct for cointegrated data and data that are neither stationary nor cointegrated. Design/methodology/approach The authors conducted Monte Carlo simulations according to Baltagi et al. (2011), Petersen (2009) and Gow et al. (2010), to analyze how regression results are affected by the possible nonstationarity of the variables of interest. Findings The results of this study suggest that biases in regression estimates can be reduced and valid inferences can be obtained by using rob

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18

Westerlund, Joakim, and Jean-Pierre Urbain. "On the implementation and use of factor-augmented regressions in panel data." Journal of Asian Economics 28 (October 2013): 3–11. http://dx.doi.org/10.1016/j.asieco.2013.02.002.

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19

León-González, Roberto, and Daniel Montolio. "Endogeneity and panel data in growth regressions: A Bayesian model averaging approach." Journal of Macroeconomics 46 (December 2015): 23–39. http://dx.doi.org/10.1016/j.jmacro.2015.07.003.

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20

Phillips, Peter C. B. "Dynamic Panel Modeling of Climate Change." Econometrics 8, no. 3 (2020): 30. http://dx.doi.org/10.3390/econometrics8030030.

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We discuss some conceptual and practical issues that arise from the presence of global energy balance effects on station level adjustment mechanisms in dynamic panel regressions with climate data. The paper provides asymptotic analyses, observational data computations, and Monte Carlo simulations to assess the use of various estimation methodologies, including standard dynamic panel regression and cointegration techniques that have been used in earlier research. The findings reveal massive bias in system GMM estimation of the dynamic panel regression parameters, which arise from fixed effect h

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21

Gluzmann, Pablo, and Demian Panigo. "Global Search Regression: A New Automatic Model-selection Technique for Cross-section, Time-series, and Panel-data Regressions." Stata Journal: Promoting communications on statistics and Stata 15, no. 2 (2015): 325–49. http://dx.doi.org/10.1177/1536867x1501500201.

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22

Paraiso, Melly, and Andrei Nicolai Pacheco. "Is the ASEAN Ready for Economic Integration? The Evidence from Panel Data Regressions." Social Sciences Development Review 8, no. 1 (2017): 1–32. https://doi.org/10.70922/qc8zwb81.

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Complementary to the commitment of building the ASeAN economic Community (AeC) is the necessity to assess productivity and economic growth across the region. The prior experience of similar economic communities posit the importance of a strong production base in order to achieve a unified growth trend. in recent years, the general growth behavior of several ASeAN member states, taken individually, have been optimistic. in this paper, the paradigm for evaluating readiness towards economic integration used a Cobb-Douglas production function to identify key factors that may affect the sustainabil

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23

Wang, Xiaojing, and Jun Yan. "Fitting semiparametric regressions for panel count survival data with an R package spef." Computer Methods and Programs in Biomedicine 104, no. 2 (2011): 278–85. http://dx.doi.org/10.1016/j.cmpb.2010.10.005.

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24

Grieser, William D., and Charles J. Hadlock. "Panel-Data Estimation in Finance: Testable Assumptions and Parameter (In)Consistency." Journal of Financial and Quantitative Analysis 54, no. 1 (2018): 1–29. http://dx.doi.org/10.1017/s0022109018000996.

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We investigate the strict-exogeneity assumption, a necessary condition for estimator consistency in many finance panel-data applications. We outline tests for strict exogeneity in both traditional (non–instrumental variable (IV)) and IV settings. When we apply these tests in common traditional finance panel regressions, we find that the strict-exogeneity assumption is often strongly rejected, suggesting large inference errors. We test for strict exogeneity in specific finance panel-data IV settings and illustrate the potential for these tests to help confirm, or rule out, the validity of commo

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25

Ghosh, Indradeep. "The Relation between Trade and FDI in Developing Countries -- A Panel Data Approach." Global Economy Journal 7, no. 3 (2007): 1850114. http://dx.doi.org/10.2202/1524-5861.1272.

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Using panel data for the period 1970-97, I examine the relation between a developing country's trade openness and the stock of its FDI liabilities. The paper makes two contributions. First, I find that trade openness is positively correlated with FDI liabilities, with or without country fixed effects. Moreover, this correlation remains robust to the inclusion of additional variables on the right hand side, such as GDP per capita, inflation, institutional quality, macroeconomic volatility and measures of capital controls. Secondly, I show that the source of this correlation is causality from FD

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26

Sufian, Fadzlan. "Determinants of Efficiency in the Malaysian Banking Sector: Evidence from Semi-parametric Data Envelopment Analysis Method." Studies in Microeconomics 4, no. 2 (2016): 151–72. http://dx.doi.org/10.1177/2321022216636443.

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This article follows Simar and Wilson’s (2007 , Journal of Econometrics, 136(1), 31–64) two-stage procedure to analyse the efficiency of the Malaysian banking sector. In the first stage, we employ the data envelopment analysis (DEA) method to compute the efficiency of individual banks during the period 1999–2008. We then use panel regressions to examine the impact of ownership on bank efficiency while controlling for the potential impacts of contextual variables. The DEA results indicate an increase in efficiency over the sample period. The results from the panel regression suggest that produc

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27

Hein, Paulo Ricardo Gherardi, Vânia Aparecida de Sá, Lina Bufalino, and Lourival Marin Mendes. "Calibrations based on near infrared spectroscopic data to estimate wood-cement panel properties." BioResources 4, no. 4 (2009): 1620–34. http://dx.doi.org/10.15376/biores.4.4.1620-1634.

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Some scientific contributions have used near infrared (NIR) spectroscopy as a rapid and reliable tool for characterizing engineered wood products. However, to our knowledge, there are no published papers that used this technique in order to evaluate wood-cement panels. The main objective of this paper was to evaluate the ability of NIR spectroscopy to estimate physical and mechanical properties in wood-cement panels. The wood-cement panels were produced using Eucalyptus grandis x E. urophylla, Pinus taeda, and Toona ciliata woods with Portland cement under different manufacturing conditions. W

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28

Çiftçioğlu, Serhan, and Murad A. Bein. "The Relationship between Financial Development and Unemployment in Selected Countries of the European Union." European Review 25, no. 2 (2017): 307–19. http://dx.doi.org/10.1017/s1062798716000600.

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This article empirically examines the relationship between alternative measures of financial development and the unemployment rate in a selected group of ten EU countries. Using annual data for the sample period of 1991–2012, we first perform different panel regressions (using averaged and non-averaged versions of data) for unemployment rate. These panel regressions are based on a regression equation that includes inflation rate and growth rate of GDP, in addition to the level of financial development, as explanatory variables. Secondly, we apply Granger causality tests to investigate the natu

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29

Fang, Zheng. "Panel Quantile Regressions and the Subjective Well-Being in Urban China: Evidence from RUMiC Data." Social Indicators Research 132, no. 1 (2015): 11–24. http://dx.doi.org/10.1007/s11205-015-1126-z.

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30

Uğurlu, Erginbay. "GROWTH AND OPENNESS RELATIONSHIP IN THE EU15: PANEL DATA ANALYSIS." Ekonomika 89, no. 2 (2010): 44–54. http://dx.doi.org/10.15388/ekon.2010.0.986.

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Conventional wisdom suggests that openness of an economy promotes economic growth. There is still argument among economists concerning how a country’s macroeconomic variables and its economic growth interact in numerous econometric studies by using panel data. This paper examines the impact of openness on economic growth for the EU-15 area in 1996–2003. In our empirical work, we have used the panel data technique which is also called longitudinal data or cross-sectional time series data. Panel data is generally concerned with choosing among three alternative regressions that are named fixed ef

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Correia, Eduardo, Rodrigo Calili, José Francisco Pessanha, and Maria Fatima Almeida. "Definition of Regulatory Targets for Electricity Non-Technical Losses: Proposition of an Automatic Model-Selection Technique for Panel Data Regressions." Energies 16, no. 6 (2023): 2519. http://dx.doi.org/10.3390/en16062519.

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Non-technical losses (NTLs) are one of the main problems that electricity distribution utilities face in developing regions such as Latin America, the Caribbean, sub-Saharan Africa, and South Asia. Particularly in Brazil, based on the socioeconomic and market variables concerning all the distribution utilities, the National Electric Energy Agency (ANEEL) has formulated several specifications of econometric models for panel data with random effects, all aimed at determining an index that reflects the difficulty of combating NTLs according to the intrinsic characteristics of each distribution ar

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32

Baltagi, Badi H., and Qi Li. "Estimating Error Component Models With General MA(q) Disturbances." Econometric Theory 10, no. 2 (1994): 396–408. http://dx.doi.org/10.1017/s026646660000846x.

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This paper provides a simple estimation method for an error component regression model with general MA(q) remainder disturbances. The estimation method utilizes the transformation derived by Baltagi and Li [3] for an error component model with autoregressive remainder disturbances, and a standard orthogonalizing algorithm for the general MA(q) model. This estimation method is computationally simple utilizing only least-squares regressions. This is important for panel data regressions where brute force GLS is in many cases not feasible.This estimation method performs well relative to true GLS i

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33

PANDA, SIDHESWAR, and RUCHI SHARMA. "DOES TECHNOLOGICAL SPECIALIZATION SPUR HIGH-TECHNOLOGY EXPORTS? EVIDENCE FROM PANEL QUANTILE REGRESSIONS." Global Economy Journal 20, no. 02 (2020): 2050013. http://dx.doi.org/10.1142/s219456592050013x.

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In view of the technological advances made by emerging economies, we revisit the role of technological specializations of different economies in determining their exports. Employing revealed technological advantage (RTA) index and revealed symmetric technological advantage (RSTA) index, this study explores the technological specialization of countries in different fields and its contribution to high-technology exports. Technological specializations are operationalized using patent data and further analyzed in context of country’s exports data of 63 countries during 2000–2013. Using panel quant

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34

Keller, Katarina R. I. "The External Social and Economic Benefits of Higher Education: Empirical Evidence from Worldwide Data." Journal of Education Finance 46, no. 4 (2021): 431–55. http://dx.doi.org/10.1353/jef.2021.a796975.

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abstract: This paper analyzes the effects of enrollment rates in higher education on its external social and economic benefits across countries globally since the 1960s. Global panel data regressions over time are used. The effects of enrollment rates in higher education have a multitude of benefits to society. Highly statistically significant effects are found, such as reducing poverty rates, infant mortality rates, and fertility rates. Enrollment rates in higher education augment political rights (i.e. democratization), as well as R&D expenditures. Equivalent regressions for sample split

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Keller, Katarina R. I. "The External Social and Economic Benefits of Higher Education: Empirical Evidence from Worldwide Data." Journal of Education Finance 49, no. 4 (2024): 422–46. https://doi.org/10.1353/jef.2024.a954740.

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abstract: This paper analyzes the effects of enrollment rates in higher education on its external social and economic benefits across countries globally since the 1960s. Global panel data regressions over time are used. The effects of enrollment rates in higher education have a multitude of benefits to society. Highly statistically significant effects are found, such as reducing poverty rates, infant mortality rates, and fertility rates. Enrollment rates in higher education augment political rights (i.e. democratization), as well as R&D expenditures. Equivalent regressions for sample split

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36

Spinelli, Daniele. "Fitting spatial autoregressive logit and probit models using Stata: The spatbinary command." Stata Journal: Promoting communications on statistics and Stata 22, no. 2 (2022): 293–318. http://dx.doi.org/10.1177/1536867x221106373.

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Starting from version 15, Stata allows users to manage data and fit regressions accounting for spatial relationships through the sp commands. Spatial regressions can be estimated using the spregress, spxtregress, and spivregress commands. These commands allow users to fit spatial autoregressive models in cross-sectional and panel data. However, they are designed to estimate regressions with continuous dependent variables. Although binary spatial regressions are important in applied econometrics, they cannot be estimated in Stata. Therefore, I introduce spatbinary, a Stata command that allows u

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37

Kusuma Indawati Halim. "The Impact Of Financial Distress, Audit Committee, And Firm Size On The Integrity Of Financial Statements." JAK (Jurnal Akuntansi) Kajian Ilmiah Akuntansi 8, no. 2 (2021): 223–33. http://dx.doi.org/10.30656/jak.v8i2.2723.

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This study aims to examine the impact of Financial Distress, Audit Committee, and Firm Size on The Integrity of Financial Statements. The integrity of financial statements can reflect the company's financial performance. The research sample obtained were based on purposive sampling technique, is including 32 consumer goods industry sectors firms listed in Indonesian Stock Exchange over the period of 2013-2017. Sources of research data are annual reports. Data analysis used descriptive statistics, classic assumption tests, estimation models, and panel data regression analysis. The panel data re

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38

Bradford, John Hamilton, and Alexander M. Stoner. "The Treadmill of Destruction in Comparative Perspective: A Panel Study of Military Spending and Carbon Emissions, 1960-2014." Journal of World-Systems Research 23, no. 2 (2017): 298–325. http://dx.doi.org/10.5195/jwsr.2017.688.

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This article analyzes a unique panel data set to assess the effect of militarism on per capita carbon dioxide emissions. We extend previous research examining the effects of military expenditures on carbon emissions by including in our analyses over 30 years of additional data. In addition, we compare our preliminary results to those obtained from other estimation procedures. Specifically, we report and visually illustrate the results of 54 cross-sectional models (one for each year) and 36 unique panel regression models on both balanced and unbalanced panels. We assess how this relationship ha

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39

Cieslik, Andrzej. "Globalization and Human Development in Post-Transition Countries: Empirical Evidence from Panel Data." Oeconomia Copernicana 5, no. 3 (2014): 7–27. http://dx.doi.org/10.12775/oec.2014.017.

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In this paper we investigate empirically the relationship between globalization and human development in post-transition countries using annual panel data for the 1971-2010 period. We show that there exists a positive and statistically significant relationship between globalization and human development in the case of unconditional regressions. This relationship remains positive and significant once the process of European and regional integration is controlled for. However, when differences in the level of economic development are taken into account the globalization variable loses its statis

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40

Gallo, Mariano, Vittorio Marzano, and Fulvio Simonelli. "Empirical Comparison of Parametric and Nonparametric Trade Gravity Models." Transportation Research Record: Journal of the Transportation Research Board 2269, no. 1 (2012): 29–41. http://dx.doi.org/10.3141/2269-04.

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A systematic comparison is made of parametric (i.e., ordinary least-squares regressions and related generalizations) and nonparametric (i.e., kernel regressions and regression trees) log-linear gravity models for reproducing international trade. Experiments were conducted to estimate a log-linear gravity model reproducing import and export trade flows in quantity between Italy and 13 world economic zones, based on a panel estimation data set. The best parametric regression model was estimated to define a baseline reference model. Some specifications of nonparametric models, belonging to the ca

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Kniesner, Thomas J., W. Kip Viscusi, and James P. Ziliak. "Policy relevant heterogeneity in the value of statistical life: New evidence from panel data quantile regressions." Journal of Risk and Uncertainty 40, no. 1 (2009): 15–31. http://dx.doi.org/10.1007/s11166-009-9084-y.

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42

Ritesh, Kumar Pandey, and Asha Ambhaikar Dr. "Data Imputation Methods and Technologies." International Journal of Trend in Scientific Research and Development 2, no. 4 (2018): 828–31. https://doi.org/10.31142/ijtsrd14113.

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We introduce a class of linear quantile regression estimators for panel data. Our framework contains dynamic autoregressive models, models with general predetermined regressors, and models with multiple individual e ects as special cases. We follow a correlated random e ects approach, and rely on additional layers of quantile regressions as a flexible tool to model conditional distributions. Conditions are given under which the model is nonparametrically identified in static or Markovian dynamic models. We develop a sequential method of moment approach for estimation, and compute the estimator

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Tinoco Zermeño, Miguel Á., Francisco Venegas Martínez, and Víctor H. Torres Preciado. "EFFECTS OF INFLATION ON FINANCIAL SECTOR PERFORMANCE: NEW EVIDENCE FROM PANEL QUANTILE REGRESSIONS." Investigación Económica 77, no. 303 (2018): 94. http://dx.doi.org/10.22201/fe.01851667p.2018.303.64156.

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<p>This paper explores the influence of inflation on the conditional distribution of financial development, an issue that has not received attention in related literature, with data from 84 countries covering the 1980-2010 period. In our data we show the presence of fixed effects, reject cross-sectional dependence in the error structure and justify poolability. Our empirical strategy employs standard and fixed-effects quantile regressions to demonstrate that the influence of inflation varies along the quantiles of the conditional finance distribution. In general, we find a consistently n

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44

Supartoyo, Yesi Hendriani. "Renewable Energy Consumption and SDG 7 Progress: The Case of MINT Countries." International Journal of Energy Economics and Policy 15, no. 3 (2025): 684–88. https://doi.org/10.32479/ijeep.19161.

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In the context of Mexico, Indonesia, Nigeria, and Turkey (MINT) countries, this study investigates the relationship between renewable energy consumption and access to clean fuels and technologies for cooking as well as access to electricity. When control variables and time-fixed effects were taken into account, panel data regressions were utilized to investigate the effects of specific SDG 7 indicators from the data of Sustainable Development Report for years 2000 – 2021, such as renewable energy consumption, access to clean fuels and technologies for cooking, and access to electricity. For th

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45

Galiński, Paweł. "Fiscal Balance Factors of the Local Government: Panel Data Evidence from OECD Countries." Ekonomia Międzynarodowa, no. 41 (December 28, 2023): 38–66. http://dx.doi.org/10.18778/2082-4440.41.03.

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Fiscal balance is perceived as a principal measure of fiscal sustainability in the local government. It also affects the budgetary response to a potential recession, determining a fiscal distress and a financial resilience. Thus, the economists conduct studies to identify factors influencing the fiscal balance at the local public level. Therefore, the aim of the paper is to examine fiscal, socio-economic, political, and institutional factors which affect the level of fiscal balance of the local government sector in Gross Domestic Product (GDP) on the basis of the OECD countries in the period 2

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Dobranschi, Marian, and Valentin Pîrvuţ. "Military Spending and Personnel Dynamics: A Panel Data Analysis of NATO Members." International conference KNOWLEDGE-BASED ORGANIZATION 31, no. 2 (2025): 20–27. https://doi.org/10.2478/kbo-2025-0044.

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Abstract This study examines the relationship between public defense expenditures and military personnel levels across 28 NATO countries from 2000 to 2021. Using fixed-effects panel regressions, we assess how total and disaggregated military spending—covering personnel, equipment, infrastructure, and other categories—affects both total armed forces (including civilians) and active military personnel. The analysis controls economic and demographic factors such as GDP (PPP), population, and net migration. Results show that increases in personnel and infrastructure spending are positively associa

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47

Polat, Ali, and Mehmet Yesilyaprak. "Export Credit Insurance and Export Performance: An Empirical Gravity Analysis for Turkey." International Journal of Economics and Finance 9, no. 8 (2017): 12. http://dx.doi.org/10.5539/ijef.v9n8p12.

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The paper attempts to find out how far Turkey’s official export credit agency, Turk Eximbank, foster export of Turkey during the years of 2000-2015 by employing an empirical trade gravity equation. We estimate different panel gravity regressions for 212 countries for the period of 16 years and the results reveal that a change in export credit insurance positively affect Turkish export, assuming other independent variables are held constant. After applying several post estimation tests we used fixed effect panel specification as the main estimation. In order to allow comparison we also run clus

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Guan, Ming. "Panel Associations Between Newly Dead, Healed, Recovered, and Confirmed Cases During COVID-19 Pandemic." Journal of Epidemiology and Global Health 12, no. 1 (2021): 40–55. http://dx.doi.org/10.1007/s44197-021-00019-z.

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Abstract Background Currently, the knowledge of associations among newly recovered cases (NR), newly healed cases (NH), newly confirmed cases (NC), and newly dead cases (ND) can help to monitor, evaluate, predict, control, and curb the spreading of coronavirus disease 2019 (COVID-19). This study aimed to explore the panel associations of ND, NH, and NR with NC. Methods Data from China Data Lab in Harvard Dataverse with China (January 15, 2020 to January 14, 2021), the United States of America (the USA, January 21, 2020 to April 5, 2021), and the World (January 22, 2020 to March 20, 2021) had b

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Sohn, Wook, and Laila Ume. "The Impact of Microfinance on Poverty Alleviation: The Case of Pakistan." Journal of Asian Development 5, no. 3 (2019): 16. http://dx.doi.org/10.5296/jad.v5i3.15165.

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This paper examines the effect of microfinance on poverty alleviation in Pakistan using district-level panel data. We conduct fixed effect panel regressions to show a statistically significant positive impact of microfinance on household income, ownership of household assets, education, and expenditure. These results suggest that the development of microfinance is an efficient tool for both welfare improvement and poverty alleviation in Pakistan.

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LEE, BUN SONG, SUNG HYO HONG, and MARK E. WOHAR. "CITY SIZE, LABOR PRODUCTIVITY AND WAGES IN KOREA." Singapore Economic Review 65, no. 04 (2017): 1073–98. http://dx.doi.org/10.1142/s0217590817500138.

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This study attempts to derive policy implications for spatially-balanced growth through empirical analysis on determinants of regional wage gaps in Korea. Combes et al. [(2008) Spatial wage disparities: Sorting Matters. Journal of Urban Economics, 63, 723–742] suggest that regional wage gaps result from the regional differences in workers’ human capital, nonhuman endowments, and agglomeration economies. The current study applies a similar two-stage estimation model to the 2006 cross-sectional data for 4009 workers from the Korean Labor Panel Survey (KLPS) performed by the Korea Labor Institute

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