Efficient IV Estimation in Nonstationary Regression

1995 ◽  
Vol 11 (5) ◽  
pp. 1095-1130 ◽  
Author(s):  
Yuichi Kitamura ◽  
Peter C.B. Phillips
Keyword(s):  
Instrumental Variables ◽  
Generalized Method Of Moments ◽  
Full Rank ◽  
Ordinary Least Squares ◽  
Small Sample ◽  
Estimation Methods ◽  
Limit Theory ◽  
Iv Estimation ◽  
Small Sample Properties ◽  
The Difference

A limit theory for instrumental variables (IV) estimation that allows for possibly nonstationary processes was developed in Kitamura and Phillips (1992, Fully Modified IV, GIVE, and GMM Estimation with Possibly Non-stationary Regressors and Instruments, mimeo, Yale University). This theory covers a case that is important for practitioners, where the nonstationarity of the regressors may not be of full rank, and shows that the fully modified (FM) regression procedure of Phillips and Hansen (1990) is still applicable. FM. versions of the generalized method of moments (GMM) estimator and the generalized instrumental variables estimator (GIVE) were also developed, and these estimators (FM-GMM and FM-GIVE) were designed specifically to take advantage of potential stationarity in the regressors (or unknown linear combinations of them). These estimators were shown to deliver efficiency gains over FM-IV in the estimation of the stationary components of a model.This paper provides an overview of the FM-IV, FM-GMM, and FM-GIVE procedures and investigates the small sample properties of these estimation procedures by simulations. We compare the following five estimation methods: ordinary least squares, crude (conventional) IV, FM-IV, FM-GMM, and FM-GIVE. Our findings are as follows, (i) In terms of overall performance in both stationary and nonstationary cases, FM-IV is more concentrated and better centered than OLS and crude IV, though it has a higher root mean square error than crude IV due to occasional outliers, (ii) Among FM-IV, FM-GMM, and FM-GIVE, (a) when applied to the stationary coefficients, FM-GIVE generally outperforms FM-IV and FM-GMM by a wide margin, whereas the difference between the latter two is quite small when the AR roots of the stationary processes are rather large; and (b) when applied to the nonstationary coefficients, the three estimators are numerically very close. The performance of the FM-GIVE estimator is generally very encouraging.

scholarly journals A Crook is a Crook . . . But is He Still a Crook Abroad? On the Effect of Immigration on Destination-Country Corruption

2015 ◽  
Vol 16 (4) ◽  
pp. 464-489 ◽  
Author(s):  
Eugen Dimant ◽  
Margarete Redlin ◽  
Tim Krieger
Keyword(s):  
Method Of Moments ◽  
Fixed Effects ◽  
Generalized Method Of Moments ◽  
Destination Country ◽  
Estimation Methods ◽  
Econometric Methodology ◽  
Migration Flows ◽  
The Difference ◽  
Method Of Moments Estimator ◽  
The Impact

AbstractThis paper analyzes the impact of migration on destination-country corruption levels. Capitalizing on a comprehensive dataset consisting of annual immigration stocks of OECD countries from 207 countries of origin for the period 1984-2008, we explore different channels through which corruption might migrate. We employ different estimation methods using fixed effects and Tobit regressions in order to validate our findings. Moreover, we also address the issue of endogeneity by using the Difference- Generalized Method of Moments estimator. Independent of the econometric methodology, we consistently find that while general migration has an insignificant effect on the destination country’s corruption level, immigration from corruption-ridden origin countries boosts corruption in the destination country. Our findings provide a more profound understanding of the socioeconomic implications associated with migration flows.

Ownership concentration, earnings management and stock market liquidity: evidence from Malaysia

2017 ◽  
Vol 17 (3) ◽  
pp. 490-510 ◽  
Author(s):  
Hamdan Amer Al-Jaifi
Keyword(s):  
Stock Market ◽  
Earnings Management ◽  
Instrumental Variables ◽  
Generalized Method Of Moments ◽  
Market Liquidity ◽  
Ownership Concentration ◽  
Estimation Methods ◽  
Content Type ◽  
Stock Market Liquidity ◽  
The Impact

Purpose This paper aims to examine whether ownership concentration and earnings management affect the stock market liquidity of Malaysian firms. Design/methodology/approach This study uses a sample of 2,020 yearly firm observations in Bursa Malaysia over the period 2009-2012. The ordinary least square regression is used to examine the relationships. The study undertakes a sensitivity test by regressing the main study variables by using different measurements. Another robustness test is then used, where a regression based on the change in variables and a one-year lag of the independent variables are used. Furthermore, to alleviate the concern of possible endogeneity, the simultaneity and reverse causality are checked using the lag of the dependent variable, fixed effect regression, two-stage least squares using the instrumental variables and the generalized method of moments using instrumental variables analysis. Findings The study finds that firms with a high level of ownership concentration have discrepancies in information between informed and uninformed traders, which impair the stock market liquidity. In addition, this study finds that firms with high earnings management experience greater liquidity. A possible explanation for this is that firms might manage earnings to convey private information to enhance the information content of the earnings. Overall, the evidence suggests that manipulating earnings signals information informatively, particularly in a country with a higher level of ownership concentration and a higher likelihood of expropriating minority shareholders. Originality/value This study enriches the limited empirical research devoted to the impact of earnings management and ownership concentration on stock market liquidity especially in the context of emerging economies. The findings of this study are robust to alternative liquidity measurements, to alternative estimation methods, and to endogeneity bias.

Intergenerational Income Elasticities, Instrumental Variable Estimation, and Bracketing Strategies

2020 ◽  
Vol 50 (1) ◽  
pp. 1-46
Author(s):  
Pablo A. Mitnik
Keyword(s):  
Instrumental Variable ◽  
Income Elasticity ◽  
Geometric Mean ◽  
Panel Study ◽  
Generalized Method Of Moments ◽  
Ordinary Least Squares ◽  
Point Estimate ◽  
Set Estimation ◽  
Iv Estimation ◽  
Short Run

The fact that the intergenerational income elasticity (IGE)—the workhorse measure of economic mobility—is defined in terms of the geometric mean of children’s income generates serious methodological problems. This has led to a call to replace it with the IGE of the expectation, which requires developing the methodological knowledge necessary to estimate the latter with short-run measures of income. This article contributes to this aim. The author advances a “bracketing strategy” for the set estimation of the IGE of the expectation that is equivalent to that used to set estimate (rather than point estimate) the conventional IGE with estimates obtained with the ordinary least squares and instrumental variable (IV) estimators. The proposed bracketing strategy couples estimates generated with the Poisson pseudo–maximum likelihood estimator and a generalized method of moments IV estimator of the Poisson or exponential regression model. The author develops a generalized error-in-variables model for the IV estimation of the IGE of the expectation and compares it with the corresponding model underlying the IV estimation of the conventional IGE. By considering both bracketing strategies from the perspective of the partial-identification approach to inference, the author specifies how to construct confidence intervals for the IGEs, in particular when the upper bound is estimated more than once with different sets of instruments. Finally, using data from the Panel Study of Income Dynamics, the author shows that the bracketing strategies work as expected and assesses the information they generate and how this information varies across instruments and short-run measures of parental income. Three computer programs made available as companions to the article make the set estimation of IGEs, and statistical inference, very simple endeavors.

scholarly journals Using Samples of Unequal Length in Generalized Method of Moments Estimation

2013 ◽  
Vol 48 (1) ◽  
pp. 277-307 ◽  
Author(s):  
Anthony W. Lynch ◽  
Jessica A. Wachter
Keyword(s):  
Method Of Moments ◽  
Generalized Method Of Moments ◽  
Small Sample ◽  
Estimation Methods ◽  
Full Sample ◽  
Predictive Regressions ◽  
Monte Carlo Experiments ◽  
International Data ◽  
Method Of Moments Estimation ◽  
Unequal Length

AbstractThis paper describes estimation methods, based on the generalized method of moments (GMM), applicable in settings where time series have different starting or ending dates. We introduce two estimators that are more efficient asymptotically than standard GMM. We apply these to estimating predictive regressions in international data and show that the use of the full sample affects inference for assets with data available over the full period as well as for assets with data available for a subset of the period. Monte Carlo experiments demonstrate that reductions hold for small-sample standard errors as well as asymptotic ones.

scholarly journals Instrumental Variables and GMM: Estimation and Testing

2003 ◽  
Vol 3 (1) ◽  
pp. 1-31 ◽  
Author(s):  
Christopher F. Baum ◽  
Mark E. Schaffer ◽  
Steven Stillman
Keyword(s):  
Instrumental Variables ◽  
Method Of Moments ◽  
Diagnostic Tests ◽  
Generalized Method Of Moments ◽  
Test Procedures ◽  
Gmm Estimation ◽  
Iv Estimation ◽  
Gmm Estimates

We discuss instrumental variables (IV) estimation in the broader context of the generalized method of moments (GMM), and describe an extended IV estimation routine that provides GMM estimates as well as additional diagnostic tests. Stand-alone test procedures for heteroskedasticity, overidentification, and endogeneity in the IV context are also described.

scholarly journals Handling heteroskedasticity in labour demand functions of athletes

2018 ◽  
Vol 4 (2) ◽  
pp. 47-56
Author(s):  
Gábor Rappai ◽  
Diána Ivett Fűrész
Keyword(s):  
Least Squares ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Estimation Methods ◽  
Demand Functions ◽  
Demand Curves ◽  
The Difference ◽  
Sport Events ◽  
Parameter Estimation Methods ◽  
Sport Economics

AbstractBased on previous research it can be stated that modelling sport economics related demand curves (e.g. demand for sport events and athletes) is different from other types of modelling. The difference lies in the fact that some parts of the demand curves are nearly horizontal in case of sport goods and nearly vertical in case of athletes, because the price of sport events is inflexible and at the same time, salaries of top athletes are extremely flexible. This study investigates parameter estimation methods appropriate for the relevant demand functions of sport economics. In this cases the generally used ordinary least squares estimator is less robust, so the weighted least squares estimators are able to handle heteroskedasticity. If the distribution of the variables is known, the Newey-West heteroscedasticity corrected estimates give even stronger results. The empirical study analyses footballer transfer fees in top European leagues and identifies a threshold at which the traditional supply-demand functions are not appropriate. According to the results, word class athletes, in a way, can be considered prestige goods for which demand may be irrational.

Corporate social responsibility and financial performance in Saudi Arabia

2018 ◽  
Vol 44 (6) ◽  
pp. 648-664 ◽  
Author(s):  
Husam-Aldin Nizar Al-Malkawi ◽  
Saima Javaid
Keyword(s):  
Saudi Arabia ◽  
Corporate Social Responsibility ◽  
Social Responsibility ◽  
Financial Performance ◽  
Generalized Method Of Moments ◽  
Ordinary Least Squares ◽  
Estimation Methods ◽  
Content Type ◽  
Corporate Social ◽  
The Impact

PurposeThe purpose of this paper is to investigate the impact of corporate social responsibility (CSR) on corporate financial performance (CFP) using Zakat as a measure for CSR.Design/methodology/approachThe study examines a sample of 107 non-financial firms listed on the Saudi Arabia stock market over a ten-year period from 2004 to 2013. The authors use the generalized method of moments framework developed by Arellano and Bover (1995) and Blundell and Bond (1998). In addition, for comparison purpose and as a robustness check, the present study uses other panel data techniques including fixed effects model, random effects model (and pooled ordinary least squares.FindingsThe results reveal that there is a strong positive relationship between CSR (Zakat) and CFP. This suggests that Zakat contribute positively to both firm’s profitability and value and can be considered as a win-win strategy to maximize returns and improve performance while considering the society as a whole. The results are robust to alternative econometric estimation methods.Practical implicationsThe companies in Islamic economies can effectively and efficiently implement the basic Shari’a Law of paying Zakat, as a successful measure to implement CSR program, thus benefiting the society by narrowing the gap between the haves and have-nots, that, in turn, leads the company to achieve successfully its short-term as well as long-term goals and enhances the value of the firm in the market. Moreover, corporations are generally encouraged to adopt CSR because of its perceived benefits to both macro- and micro-performances.Originality/valueTo the best of the author’s knowledge, this is the first empirical study attempting to examine CSR-CFP relationship within Saudi context employing Zakat as a proxy for CSR. Additionally, the paper provides support for the stakeholder theory from an Islamic perspective.

Sign in / Sign up

Export Citation Format

Share Document