Two-step Generalized Method Of Moments Estimator Research Articles

UTJECAJ TERORISTIČKIH NAPADA NA PRILJEV IZRAVNIH STRANIH ULAGANJA U TRANZICIJSKIM ZEMLJAMA

The main aim of the paper is to empirically measure the impact of terrorism and other (institutional, economic, natural) factors on the foreign direct investments (FDI inward stock) of transition economies in the world. Methodology includes the application of two-step system GMM (Generalized Method of Moments) estimator of dynamic panel analysis. The research covers a group of 16 countries from 2000 to 2016. Research findings confirm that terrorist incidents, economic and institutional variables affect FDI inward stock of transition economies. It can be concluded that institutional variables (Government effectiveness, control of corruption) recorded the most significant impact on the inward FDI stock in the transition economies of the global economy. From the results, we can see the international competitiveness of transition countries about the influence of the variables of terrorism and other relevant model variables on foreign direct investments (FDI).

The effect of corruption on FDI and its modes of entry

PurposeThe purpose of this paper is to empirically investigate the impact of corruption on foreign direct investment (FDI) and its two major modes of entry: greenfield investment (greenfield) and cross-border mergers and acquisitions (M&As).Design/methodology/approachData are collected from 131 countries. Modern econometric techniques, including the generalized method of moments (GMM) estimator, two-stage least square estimator and two-step system GMM estimator, are used to evaluate the impact of corruption on FDI activities.FindingsThe empirical results illustrate that corruption is a deterioration factor that significantly hinders FDI inflows. However, this finding turns out to be contradictory when the two major components of FDI – greenfield investment and cross-border M&As – are separately examined. Specifically, while corruption consistently discourages cross-border M&As over time, it appears to exert positive effect on greenfield investments.Originality/valueThis is among the first to empirically examine the impact of corruption on FDI and its modes of entry in a number of countries spanning different time windows. In this sense, this paper also captures the changing nature of societies and economic conditions overtime and, therefore, enable academic researchers, policy-makers and business practitioners to draw broad inferences from the empirical results.

The determinants of intermediation margins in Islamic and conventional banks

Purpose The distinctive feature of Islamic financial intermediation is its foundation on profit-and-loss sharing which reinforces solidarity and fraternity between partners. Thus, the bank margin and its determinants may differ between Islamic and conventional banks (CBs). The purpose of this paper is to empirically assess the main factors that explain the bank margin in a panel of Islamic and CBs operating in the Middle East and North Africa (MENA) region. This study will permit to identify the common and the specific determinants of the intermediation margins in dual banking systems. Design/methodology/approach The authors use a dynamic panel approach. The empirical analysis is carried out for a sample of 50 Islamic banks (IBs) and 126 CBs from 14 MENA countries. Findings The results reveal that net profit margins of IBs may be explained for the most part by risk aversion, inefficiency, diversification and economic conditions. With regard to CBs, their margins depend positively on market concentration and risk aversion and negatively on specialization, diversification, inefficiency and liquidity. Practical implications The significant impact of the degree of diversification on margins suggests that any policy analysis of the pricing behavior of banks should rely on its whole output. The high levels of margins in Islamic and CBs based in the MENA region may represent an obstacle to these countries to pursue their development process. Thus, policy makers in these countries should consolidate the role of capital markets and nonbanking financial institutions to provide alternative sources of funding and stimulate more competition. Social implications The positive relationship between concentration and net interest margins requires that policy makers should create competitive conditions if they want to lower the social cost of financial intermediation. The creation of competitive conditions may be achieved through encouraging the establishment of new domestic banks or the penetration of foreign banks. Originality/value The present study aims to contribute to the existing literature on the determinants of bank margins in three ways. First, the authors identify the factors that most explain bank margins for both conventional and IBs. The majority of previous studies examine the determinants of the profitability or the overall performance of banks and in particular conventional ones. Second, this paper employs two generalized method of moments (GMM) approaches introduced by Arellano and Bover (1995) and Arellano and Bond (1991). It differs from Hutapea and Kasri (2010) who employed the co-integration technique to examine the long-run relationship between Islamic and CB margins and their determinants in Indonesia. Third, unlike previous studies focusing on MENA region that use a small number of countries and a short sample period, the period of study covers 16 years from 1999 to 2014 and a large sample of countries (14 countries). This paper differs from Lee and Isa (2017) who applied the dynamic two-step GMM estimator technique introduced by Arellano and Bond (1991) to study the determinants of intermediation margins of Islamic and CBs located in Malaysia.

The Effect of Corruption on FDI and Its Modes of Entry

Purpose – The purpose of this paper is to empirically investigate the impact of corruption on foreign direct investment (FDI) and its two major modes of entry: greenfield investment (greenfield) and cross-border mergers and acquisitions (M&As). Design/methodology/approach – Data is collected from 131 countries. Modern econometric techniques, including the generalized method of moments (GMM) estimator, two-stage least square estimator, and two-step system GMM estimator, are utilized to evaluate the impact of corruption on FDI activities. Findings – The empirical results illustrate that corruption is a deterioration factor that significantly hinders FDI inflows. However, this finding turns out to be contradictory when the two major components of FDI – greenfield investment and cross-border M&As, are separately examined. Specifically, while corruption consistently discourages cross-border M&As over time, it appears to exert positive effect on greenfield investments. Originality/value – This is among the first to empirically examine the impact of corruption on FDI and its modes of entry in a number of countries spanning different time windows. In this sense, this study also captures the changing nature of societies and economic conditions overtime, and therefore, enable academic researchers, policy-makers, and business practitioners to draw broad inferences from the empirical results.

Fixed-smoothing asymptotics in the generalized empirical likelihood estimation framework

This paper concerns the fixed-smoothing asymptotics for two commonly used estimators in the generalized empirical likelihood estimation framework for time series data, namely the continuous updating estimator and the maximum blockwise empirical likelihood estimator. For continuously updating generalized method of moments (GMM) estimator, we show that the results for the two-step GMM estimator in Sun (2014a) continue to hold under suitable assumptions. For continuous updating estimator obtained through solving a saddle point problem (Newey and Smith, 2004) and the maximum blockwise empirical likelihood estimator (Kitamura, 1997), we show that their fixed-smoothing asymptotic distributions (up to an unknown linear transformation) are mixed normal. Based on these results, we derive the asymptotic distributions of the specification tests (including the over-identification testing and testing on parameters) under the fixed-smoothing asymptotics, where the corresponding limiting distributions are nonstandard yet pivotal. Simulation studies show that (i) the fixed-smoothing asymptotics provides better approximation to the sampling distributions of the continuous updating estimator and the maximum blockwise empirical likelihood estimator as compared to the standard normal approximation. The testing procedures based on the fixed-smoothing critical values are more accurate in size than the conventional chi-square based tests; (ii) the continuously updating GMM estimator is asymptotically more efficient and the corresponding specification tests are generally more powerful than the other two competitors. Finite sample results from an empirical data analysis are also reported.

Fixed-Smoothing Asymptotics in a Two-Step Generalized Method of Moments Framework

This paper develops the fixed-smoothing asymptotics in a two-step generalized method of moments (GMM) framework. Under this type of asymptotics, the weighting matrix in the second-step GMM criterion function converges weakly to a random matrix and the two-step GMM estimator is asymptotically mixed normal. Nevertheless, the Wald statistic, the GMM criterion function statistic, and the Lagrange multiplier statistic remain asymptotically pivotal. It is shown that critical values from the fixed-smoothing asymptotic distribution are high order correct under the conventional increasing-smoothing asymptotics. When an orthonormal series covariance estimator is used, the critical values can be approximated very well by the quantiles of a noncentral F distribution. A simulation study shows that statistical tests based on the new fixed-smoothing approximation are much more accurate in size than existing tests.

THE ASYMPTOTIC PROPERTIES OF THE SYSTEM GMM ESTIMATOR IN DYNAMIC PANEL DATA MODELS WHEN BOTHNANDTARE LARGE

In this paper, we derive the asymptotic properties of the system generalized method of moments (GMM) estimator in dynamic panel data models with individual and time effects when bothNandT, the dimensions of cross-section and time series, are large. Specifically, we show that the two-step system GMM estimator is consistent when a suboptimal weighting matrix where off-diagonal blocks are set to zero is used. Such consistency results theoretically support the use of the system GMM estimator in largeNandTcontexts even though it was originally developed for largeNand smallTpanels. Simulation results indicate that the largeNand largeTasymptotic results approximate the finite sample behavior reasonably well unless persistency of data is strong and/or the variance ratio of individual effects to the disturbances is large.

Banking regulation and supervision: can it enhance stability in Europe?

Purpose – This paper aims to find the effects of regulatory and supervisory policies on bank risk-taking. The same regulation and supervision have different effects on bank risk-taking depending on influence factors. These factors were considered and a sample of the largest European banks from France, Germany, UK, Italy, Spain and Greece was used over the period 2005-2011. Design/methodology/approach – In this paper, the author analyses the effects of regulation and supervision on risk-taking. The author uses a sample of the biggest banks from six European countries (France, UK, Germany, Italy, Spain and Greece) over the period 2005-2011. Because the applicable entry of IFRS was in 2005, thus data of European banks are not available before this date. For each country in the sample, the 10 largest banks (defined by total assets) that lend money to firms were identified. The author does not include central banks or postal banks, which generally do not lend money to firms and are described as non-banking institutions (La Porta et al., 2002). Findings – It was found that restrictions on bank activities, supervisors’ power and capital adequacy decrease risk-taking. Thus, regulation and supervision enhance bank’s stability. While, deposit insurance increases the risk due to its association to moral hazard. Finally, it was found that strengthening regulatory and supervisory framework raises the risk-taking and weakens the stability of European banks. Originality/value – The author contributes to existing empirical analyses in three ways. First, the existing literature has drawn a lot of attention on US banks. However, the purpose of this paper is to examine the biggest banks of three European leaders (France, Germany and UK) and three more European countries influenced by the recent crisis (Spain, Italy and Greece) over the period 2005-2011. Second, most studies focus mainly on the relationship between regulation and profitability, yet seldom on the relationship between regulation, supervision and risk-taking. The author focuses on this relationship. Third, this study applies the two-step dynamic panel data approach suggested by Blundell and Bond (1998) and also uses dynamic panel generalized method of moments (GMM) method to address potential problems. The two-step GMM estimator that the author uses is generally the most efficient.

AN EFFICIENT LINEAR GMM ESTIMATOR FOR THE COVARIANCE STATIONARY AR(1)/UNIT ROOT MODEL FOR PANEL DATA

This paper considers generalized method of moments (GMM) estimation of the inclusive panel AR(1) model that contains the covariance stationary panel AR(1) model and the panel AR(1) model with a unit root as special cases. The paper presents a two-step optimal linear GMM (OLGMM) estimator for the inclusive model that is asymptotically equivalent to the optimal nonlinear GMM estimator of Ahn and Schmidt (1997, Journal of Econometrics 76, 309–321) when the data are covariance stationary. Next the paper derives the asymptotic distribution of the OLGMM estimator when the model has a unit root under a variety of assumptions about the initial observations and the initial estimator. It is shown that in most cases the OLGMM estimator is superconsistent. In addition it is shown that the iterated OLGMM estimator is superefficient when the variance of the initial observations is finite and fixed, i.e., small compared to the cross-sectional dimension of the panel. The paper also conducts a Monte Carlo study in which the finite-sample properties of various GMM estimators for the inclusive panel AR(1) model are compared.I thank Steve Bond and Frank Windmeijer for kindly making one of their computer programs available to me. I also thank two anonymous referees and a co-editor for very helpful comments. This research was funded by the ESRC under grant R000239139.

GMM estimation of a maximum entropy distribution with interval data

We develop a generalized method of moments (GMM) estimator for the distribution of a variable where summary statistics are available only for intervals of the random variable. Without individual data, one cannot calculate the weighting matrix for the GMM estimator. Instead, we propose a simulated weighting matrix based on a first-step consistent estimate. When the functional form of the underlying distribution is unknown, we estimate it using a simple yet flexible maximum entropy density. Our Monte Carlo simulations show that the proposed maximum entropy density is able to approximate various distributions extremely well. The two-step GMM estimator with a simulated weighting matrix improves the efficiency of the one-step GMM considerably. We use this method to estimate the U.S. income distribution and compare these results with those based on the underlying raw income data.

RELIABLE INFERENCE FOR GMM ESTIMATORS? FINITE SAMPLE PROPERTIES OF ALTERNATIVE TEST PROCEDURES IN LINEAR PANEL DATA MODELS

ABSTRACT We compare the finite sample performance of a range of tests of linear restrictions for linear panel data models estimated using the generalized method of moments (GMM). These include standard asymptotic Wald tests based on one-step and two-step GMM estimators; two bootstrapped versions of these Wald tests; a version of the two-step Wald test that uses a finite sample corrected estimate of the variance of the two-step GMM estimator; the LM test; and three criterion-based tests that have recently been proposed. We consider both the AR(1) panel model and a design with predetermined regressors. The corrected two-step Wald test performs similarly to the standard one-step Wald test, whilst the bootstrapped one-step Wald test, the LM test, and a simple criterion-difference test can provide more reliable finite sample inference in some cases.

A finite sample correction for the variance of linear efficient two-step GMM estimators

Monte Carlo studies have shown that estimated asymptotic standard errors of the efficient two-step generalized method of moments (GMM) estimator can be severely downward biased in small samples. The weight matrix used in the calculation of the efficient two-step GMM estimator is based on initial consistent parameter estimates. In this paper it is shown that the extra variation due to the presence of these estimated parameters in the weight matrix accounts for much of the difference between the finite sample and the usual asymptotic variance of the two-step GMM estimator, when the moment conditions used are linear in the parameters. This difference can be estimated, resulting in a finite sample corrected estimate of the variance. In a Monte Carlo study of a panel data model it is shown that the corrected variance estimate approximates the finite sample variance well, leading to more accurate inference.