Difference GMM Research Articles

Impact of financial development and energy consumption on environmental degradation in 184 countries using a dynamic panel model.

This study aimed to examine the impact of financial development and energy consumption on CO2 emissions by employing balanced panel data from the period 1990-2017 for 184 countries worldwide. This study applied seemingly unrelated regression (SUR), two-step difference, and the system GMM model for data analysis. The examined results of SUR, two-step difference, and system GMM show that energy consumption positively impacts the CO2 emissions worldwide; on the other hand, the examined results of two-step difference and the system GMM model indicate that financial development helps to reduce the CO2 emissions and the results of SUR indicate that financial development positively impacts the CO2 emissions. The examined results regarding economic growth indicate a positive effect on the CO2 emission and the square of economic growth verifies the validly of the environmental Kuznets curve in 184 countries. This study has significant implications for policy makers with regard to environment improvement, clean energy conservation, and an efficient financial system. Further directions are suggested based on the examined results.

The nonlinearity of exchange rate pass‐through on currency invoice: A quantile, generalized method of moments and threshold effect‐test from sub‐Sahara African economies

AbstractThis article explores the existence of the asymmetric effect of exchange rate pass‐through on exporter's currency‐invoice in 44 resources abundant sub‐Saharan African countries over the period 2008–2017. The investigation is carried‐out using asymmetric threshold regression developed by Hansen (1999, 2000) through 1,000 bootstrapping replications and the grid search. Our empirical results based on 44 SSA countries reveal a significant single threshold of 2.60%. We consider the effects of real income, openness, and the terms of trade on the real exchange rate measures, which exhibited a significant effect on the exporter's currency‐invoicing when exceeds beyond the threshold's values. Furthermore, we also consider the distribution of the effect of the regressors on currency‐invoice and found significant quantile coefficients appeared differently from the OLS coefficients. The quantile estimates for the exchange rate pass‐through reveal an asymmetry and gradual decay on the real exchange rate coefficients from 10th quantile. Hence, the pass‐through on the exporter's currency‐invoice is incomplete. Besides, the dynamic panel two‐step difference GMM estimators revealed statistically significant short‐run and long‐run impacts of ERPT on exporter's currency‐invoice in 44 SSA countries. In policy terms, the central banks in SSA countries should monitor the developments in the foreign exchange market to design appropriate policies to resist external sector shock from international trade.

Technology Import and China's Innovation Capability: Does Institutional Quality Matter?

With the rapid growth of China's economy, technology import plays a crucial role in enhancing regional innovation capability. Based on inter-provincial panel data from 2007 to 2016, this paper uses three benchmark linear regression models of Ordinary Least Squares (OLS), Difference-Generalized Method of Moments (DIFF-GMM), and System-Generalized Method of Moments (SYS-GMM) to explore the improvement of China's regional innovation capability by technology import. Then, the regional institutional quality level is measured from the three dimensions of politics, economy, and law, and the two-step difference GMM threshold panel model is used to analyze the effect of technology import on regional innovation capability under different institutional quality conditions. The results show that: (1) In the benchmark linear regression model, technology import has a significant role in promoting regional innovation capability. (2) With the rise of regional corruption, the quality of political institution declines, and the promotion effect of technology import on regional innovation ability is weakened. (3) The improvement of the marketization level and intellectual property protection level strengthen the role of technology introduction in promoting regional innovation capability. On the contrary, in regions with low economic and legal institutional quality, technology import has no significant impact on regional innovation capability.

Economic policy uncertainty and bank credit growth: Evidence from European banks

Using a sample of 2977 private and listed banks in the EU-5 countries (the United Kingdom, Germany, Spain, Italy, France) for the years 2009–2018, this paper explores the impact of Economic Policy Uncertainty (EPU) on credit growth. Using panel data fixed effects methodology and controlling for endogeneity using two-step difference GMM estimators, our findings indicate that uncertainty in economic policies hampers the credit growth of European banks. Our bank type-based analyses indicate that the effect is mainly valid for cooperative banks. Additional analyses imply that the negative impact of EPU on credit growth is more pronounced in civil law countries, increases with debt maturity, and weakens for banks with a larger number of employees and branches. Furthermore, the unfavorable effects are stronger in well-capitalized banks, banks with foreign subsidiaries, and banks with a higher share of wholesale funding. We also provide several policy implications for different economic actors.

Export product diversification and energy efficiency: Empirical evidence from OECD countries

The present study explores the important contributors of energy efficiency in OECD countries, by taking the energy intensity and carbon intensity as a proxy of energy efficiency. Notably, we study the role of three indicators of export diversification (export product diversification, extensive margin and intensive margin) for energy intensity and carbon intensity in 29 OECD countries, which further allow us to draw new and innovative conclusions. In doing so, we use the data from 1990 to 2015 and employ alternative panel data estimations; sequential estimation, panel quantile regressions, system GMM and difference GMM, for an in-depth and detailed empirical analysis. In our empirical analysis, we robust check the impacts of export diversification on carbon intensity and investigate the role of institutional factors for energy intensity. The empirical outcomes provide robust evidence that all three indicators of export diversification help to reduce energy intensity and might be used as a policy factor in improving energy efficiency and sustainable environment. The empirical evidence further reports practical implications for policymakers and environmental scientists to achieve the greener growth, energy efficiency and sustainable development goals (SDG's) of OECD countries.

Inflation‐Output Trade‐Off in South Africa: Is the Phillips Curve Symmetric?

AbstractThis study sets out to investigate whether the inflation‐output trade‐off in South Africa is symmetric or asymmetric; and if asymmetric, whether it is convex or concave. A New Keynesian dynamic stochastic general equilibrium model calibrated on South African data reveals that a negative demand shock reduces inflation and output while a positive demand shock of the same magnitude leads to a smaller increase in inflation and a larger increase in output, indicating that the inflation–output relationship in the country is concave asymmetric. These findings corroborate estimation results of the inflation‐expectations augmented Phillips curve conducted using difference GMM on quarterly data.

MOVING OBJECT DETECTION METHOD OF VIDEO SATELLITE BASED ON TRACKING CORRECTION DETECTION

Abstract. It is the focus of current research that how to realize high precision and real-time dynamic monitoring and tracking of moving targets by video satellites because of instantaneous and dynamic continuous observation of targets in a certain area by the video satellites. The existing detection and tracking methods for moving objects have target misdetection and missed detection, which reduces the accuracy of moving object detection. In this paper, a Tracking Correction Detection Correction (TCD) method is proposed to solve these problems. Firstly, the background model is established by using the improved ViBe target detection algorithm, and the moving target mask is obtained by adaptive threshold calculation. By using pyramid structure iterative algorithm, the moving object can be classified as noise or real object according to the set of detection results of different detection windows. The high-order correlation vector tracking method is used to modify the detection result of the moving target acquired in the previous frame, and finally the accurate detection result of the moving target is obtained. The comparison analysis between the frame difference (FD) method, GMM method, ViBe method and TCD method shows that the TCD method has better robustness for noise, light and background dynamic changes, and the test results of TCD method are more complete and the real-time is better. It is proved by this work that the accuracy of the target detection of TCD method has reached 85%, which has a high engineering application value.

Dynamic Panel Modeling of Climate Change

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 heterogeneity across individual station level observations. Difference GMM and Within Group (WG) estimation have little bias and WG estimation is recommended for practical implementation of dynamic panel regression with highly disaggregated climate data. Intriguingly, from an econometric perspective and importantly for global policy analysis, it is shown that in this model despite the substantial differences between the estimates of the regression model parameters, estimates of global transient climate sensitivity (of temperature to a doubling of atmospheric CO2) are robust to the estimation method employed and to the specific nature of the trending mechanism in global temperature, radiation, and CO2.

Re-examining the determinants of capital structure in Nigeria

PurposeThe paper investigates the determinants of capital structure and the speed of adjustment of capital structure decisions of Nigerian firms.Design/methodology/approachThe paper adopts three methods: difference GMM, system GMM and stochastic frontier analysis (SFA).FindingsThe empirical results show that firms' efficiency affects the capital structure decisions of Nigerian firms. At the same time, short-term debt has a higher speed of adjustment in the context of Nigerian firms. The roles of other control variables are established in the paper.Social implicationsNigerian firms should adopt short-term debt in order to achieve their targeted debt levels. Managers of Nigerian firms are also advised to be more efficient in order to attract higher performance.Originality/valueThe paper is the first literature to measure the efficiency of firms using SFA method. Extant studies in the literature have neglected the determinant while four papers that adopt the determinant data envelope analysis (DEA) method. This is also the first study to document the speed of adjustment in capital structure decisions in the context of Nigerian firms.

Demokrasiye Geçiş ve Ekonomide Yapısal Dönüşüm Arasındaki İlişki

There are several theoretical and empirical papers on the structural transformation but there is not a study relating structural transformation with the political regime switch in the country. This paper aims to fill the gap in relevant literature by empirically examining the linkage between the political regime switch and the structure of the economy. The main purpose of this paper is to explore the impact of the political regime switch on the share of the agricultural value added in the GDP. Due to endogeneity issues, Difference GMM methodology is used to test the hypothesis that the democratization leads to the structural transformation of the economy by using data for 43 countries over the period from 1970-2016. The estimation results confirm that the share of agricultural value in total value added is higher when the country is ruled by an autocratic system rather than a democratic system. Moreover, the estimation results indicate that per capita GDP, arable land, and trade openness have a negative significant, whereas financial development, fertility, and population have a positive significant impact on the value added share of agriculture.

Natural resources, tourism development, and energy-growth-CO2 emission nexus: A simultaneity modeling analysis of BRI countries

The empirical investigation of tourism and natural resources in energy-growth-CO2 emission nexus is carried out in simultaneous equations framework for 51 “Belt & Road Initiative (BRI) countries” over 1990–2016. The dependent variables in four systems of equations are income, CO2 emission, energy use, and tourism development index. Empirics from difference and system GMM diagnosed the feedback effect between energy use and income; also validated energy push CO2 emission in conjunction with EKC for BRI countries. The results supported bidirectional causality between tourism and income; moreover, tourism push emission hypothesis validated for BRI countries. On the other hand, natural resources are contributing to tourism development, energy use, and CO2 emission in BRI countries. Additionally, natural resources are contributing negatively and significantly to income, thus obeying the natural resource curse phenomenon. So, the allocation of funds on green infrastructure are required to improve the environmental quality and benefit through green tourism. Moreover, the implementation of conservation policies on “natural resources” can help the GDP growth, environmental quality, and tourism sector on a single platform.

Determinants of capital structure: evidence from Malaysian firms

PurposeThe purpose of this paper is to examine the determinants of capital structure using a dataset of firms in Malaysia.Design/methodology/approachThis paper carries out a panel data analysis of 8,270 observations from 827 listed non-financial firms on the Malaysia stock market over the period 2008–2017. To estimate the model and analyse the data collected from the DataStream and World Bank databases, the authors use static panel estimation techniques as well as two-step difference and system dynamic GMM estimator.FindingsThe results show that profitability, growth opportunity, tax-shield, liquidity and cash flow volatility have a negative and significant impact on debt measures. However, the effects of collateral, non-debt tax and earnings volatility on measures of debt are positive and significant. In addition, firm size, firm age, inflation rate and interest rate are important determinants of the present value of debt. The results also show a significant inverse U-shaped relationship between the firm's age and its capital structure. In general, the results support the proposition advocated by the pecking order and trade-off theories.Practical implicationsThe results of this study necessitate formulation of various policy measures that can counter the effects of debt on firms.Originality/valueThe present study is among the earliest to use both the book and market value measures of capital structure. It also uses three proxies for each: total debt, long-term debt and short-term debt. It incorporates earning volatility and cash flow volatility as new independent variables in the model. These variables have not previously been used together with both book and market value measures of capital structure. The study also examines the non-monotonic relationship between firm's age and capital structure using a quadratic regression method. It applies both static panel techniques and dynamic GMM estimation techniques to analyse the data.

Do Social Factors Affect Poverty? A Dynamic Panel Data Analysis of 23 Selected Developing Countries

This research paper aims at investigating the social factors affecting poverty in selected developing countries which was hardly been investigated, yet. We incorporated income poverty index (poverty headcount ratio and poverty gap) and human poverty index as dependent variables, while social factors have been used as explanatory variables, through 1997-2016, for a group of twenty three developing nations. Whereas poverty indices have been constructed through PCA (Principal Component Analysis). Pesaran and Friedman CD (Cross-Dependence) tests have been applied to confirm the occurrence of cross-dependency in the panel data, while CIPS (second generation panel unit root) test has been applied to verify stationary of the variables. Besides, different first generation panel unit root tests have also been applied to confirm stationary of the variables. We applied Pedroni panel co-integration to check for the existence of long-run linkages among the variables, while System and difference GMM (one step) techniques have been used to find dynamic effects on poverty. The results conclude that age dependency ratio showed positive and significant relationship with poverty, whereas, social globalization depicted negative and significant relationship with poverty. Nevertheless, health (life expectancy at birth) and education (primary school enrolment) have negative relationship with poverty in both income and human poverty models, while, in income poverty model, these variables have insignificant impacts and in human poverty model, they have significant associations. Similarly, population growth has positive associations with poverty in the income and human poverty models.

Effect of monetary policy on bank risk: does market structure matter?

PurposeThe purpose of this paper is to investigate the risk-taking channel of monetary policy transmission in the Chinese banking industry. This study also investigates the role of various other factors in the risk-taking channel.Design/methodology/approachThis study used panel data from 2000 to 2012, and a dynamic panel model (Difference GMM) was applied.FindingsThe empirical findings of this paper suggest that loose monetary policy rates increase bank risk-taking. Unlike previous studies, the results of this paper suggest that the bank-specific factors (size, liquidity and capitalization) do not significantly affect the risk-taking channel. However, the market structure does have a stabilizing effect on monetary policy transmission and the risk-taking channel. Higher market power weakens the risk-taking channel of monetary policy transmission.Practical implicationsOf significance to the policymakers' point of view is that loose monetary policy induces banks to take excessive risks. However, such effects can be mitigated by encouraging a proper level of market power in banking markets.Originality/valueThis study investigated the risk-taking channel of monetary policy transmission for the Chinese banking industry. Due to the unique features of the People's Bank of China (PBC, Central Bank of China) policy, this study also contributes to the literature by comparing price-based and quantity-based monetary policy tools and their effectiveness in financial stability and monetary policy transmission. Furthermore, the role of market structure is also investigated in the risk-taking channel.

Half-panel jackknife estimation for dynamic panel models

This paper extends the half-panel jackknife (HPJ) estimator to GMM models with fixed effects. The Monte Carlo results show that the HPJ significantly reduces finite-sample bias for both the difference and system GMM estimators of the dynamic panel model.

Econometric Analysis of the Impact of Taxes on Private Investment in Sub-Sahara Africa

This study examines the impact of taxation and other macroeconomic factors on private investment in sub-Saharan Africa, taking the case of East African Community (EAC) and Southern African Development Community (SADC) countries. By estimating a dynamic neo-classical investment model for developing countries using One-Step Difference GMM, the empirical results indicate that corporate income tax (CIT) and Value Added Tax (VAT) have significant and negative effect on private investment. The results also show that real interest rate is an important factor that explains the level of private investment in the EAC and SADC countries. Credit to private sector, though found to be statistically significant, the results suggests its effect is unexplainably negative and inconsistent with economic theories. The study finds no evidence, however, on the impact of personal income taxes, real Gross Domestic Product (GDP) growth rate, nominal exchange rate and inflation rate on private investment. On the policy front, the study findings indicate that, governments from the two economic blocs need to consider lowering the corporate income tax and VAT tax rates if they are to promote and attract more private investments. Lowering interest rates through the monetary policy channel is also recommended to make their economies more attractive to potential investors.

Testing initial conditions in dynamic panel data models

We propose a new framework for testing the “mean stationarity” assumption in dynamic panel data models, required for the consistency of the system GMM estimator. In our set up the assumption is obtained as a parametric restriction in an extended set of moment conditions, allowing the use of a LM test to check its validity. Our framework provides a ranking in terms of power of the analyzed test statistics, in which our approach exhibits better power than the difference-in-Sargan/Hansen test that compares system GMM and difference GMM, that is, on its turn, more powerful than the Sargan/Hansen test based on the system GMM moment conditions.

REGIONAL INCOME AND ITS CONVERGENCE IN INDONESIA

This study aims to calculate and analyze whether or not a decline occurs in regional income inequality (sigma convergence). Additionally, it attempts to examine the ability of low-income provinces to catch up the provinces with a high regional income, neither controlled nor (absolute convergence and conditional convergence). Finally, the study calculates the speed and time needed to catch up to half of the lags. The first objective of thestudy was answered by using the coefficient of variation. The second objective was answered by the First Difference GMM (FD GMM) method, and the third objective was answered by using a formula for calculating the convergence speed expressed by Feldkircher (2006), and the half convergence formula from Barro & Sala-i-Martin (1995). This research figured out that sigma convergence occurreds after divergence. The research also reported no convergence of regional income beta, in both absolute and conditional convergences. Finally, the time needed to catch up the half of the lags in non-conditional beta convergence was shorter than conditional beta convergence.

Do Firms Approach the Target Working Capital Requirement? A Case of Pakistan

Abstract The study investigates the dynamism of working capital requirement (WCR) in non-financial firms listed on the Pakistan Stock Exchange from the period of 2007 to 2013. The purpose of this research is to analyze whether firms follow the target WCR, to estimate the speed with which firms adjust towards its target WCR and to investigate the firm-specific and macroeconomic determinants of WCR. Difference GMM technique is used to analyze the speed and determinants of WCR to avoid the problems of endogeneity and unobservable heterogeneity. The study gives evidence that there is an existence of target WCR in firms of Pakistan and firm require 1.6 years to completely adjust back to target WCR. The factors which are statistically significant in the determination of WCR are the level of economic activity in the country, operating cash flow, profitability, leverage, financial distress, and financing cost. The WCR is measured by net trade cycle of a firm.

How have Mergers and Acquisitions Affected Financial Performance of Firms in Indian Manufacturing Sector?

The paper examines how mergers and acquisitions (M&As) in India after initiation of reforms in 1991 have affected firms’ financial performance. Using panel data and applying the method of difference GMM, it is found that neither market concentration nor M&As affected firms’ financial performance because of the multidirectional structure-conduct-performance relationships. Instead, interindustry differences in performance have been caused by capital intensity, efforts relating to marketing and distribution, and foreign technology. The findings suggest for a relook at the competition policies and laws, international trade, investment and technology development as they influence financial performance through market structure along with firms’ business strategies, efficiency and competitiveness.