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.

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.

Impact of Total Asset Turnover Ratios on Equity Returns: Dynamic Panel Data Analyses

2020 ◽  
Vol 27 (2) ◽  
pp. 19
Author(s):  
Jeanne-Claire Patin ◽  
Matiur Rahman ◽  
Muhammad Mustafa
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Generalized Method Of Moments ◽  
Ordinary Least Squares ◽  
Total Asset ◽  
Operating Efficiency ◽  
Positive Effects ◽  
Short Run ◽  
Asset Turnover ◽  
The Impact

This paper is an empirical exploration of the impact of total asset turnover ratios on stock returns of 1961 US public firms in different types of industries from 2001 to 2015. Stock prices are significantly influenced by operating performance of a company in efficiently utilizing its assets. For that matter, operating efficiency (as measured by total asset turnover ratio) plays a role in portfolio investment decisions. Pedroni’s heterogeneous panel co-integration procedures, associated bivariate error-correction model (ECM), dynamic ordinary least squares (DOLS) and generalized method of moments (GMM) are applied. Both stock returns and total asset turnover ratios in levels are nonstationary with I (1) behavior. Subsequently, both variables are found cointegrated. The panel ECM estimates suggest convergence of variables toward long-run equilibrium at moderate pace with short-run interactive positive feedback effects. Again, both DOLS and GMM estimates reveal short-run contemporaneous positive effects of total asset turnover ratios on stock returns in levels. In view of the findings of this study, firms should strive to improve operating efficiency, among others, to enhance competitiveness and thereby to boost their stock prices for rewarding shareholders.

Heteroskedasticity- and Autocorrelation-robust F and t Tests in Stata

2018 ◽  
Vol 18 (4) ◽  
pp. 951-980 ◽  
Author(s):  
Xiaoqing Ye ◽  
Yixiao Sun
Keyword(s):  
Method Of Moments ◽  
Instrumental Variable ◽  
Generalized Method Of Moments ◽  
Ordinary Least Squares ◽  
Type I ◽  
Variance Estimators ◽  
Normal Approximations ◽  
Chi Squared ◽  
Smoothing Parameters ◽  
Type Ii Errors

In this article, we consider time-series, ordinary least-squares, and instrumental-variable regressions and introduce a new pair of commands, har and hart, that implement more accurate heteroskedasticity- and autocorrelation-robust (HAR) F and t tests. These tests represent part of the recent progress on HAR inference. The F and t tests are based on the convenient F and t approximations and are more accurate than the conventional chi-squared and normal approximations. The underlying smoothing parameters are selected to target the type I and type II errors, which are the two fundamental objects in every hypothesis testing problem. The estimation command har and the postestimation test command hart allow for both kernel HAR variance estimators and orthonormal-series HAR variance estimators. In addition, we introduce another pair of new commands, gmmhar and gmmhart, that implement the recently developed F and t tests in a two-step generalized method of moments framework. For these commands, we opt for the orthonormal-series HAR variance estimator based on the Fourier bases because it allows us to develop convenient F and t approximations as in the first-step generalized method of moments framework. Finally, we present several examples to demonstrate these commands.

scholarly journals Impact of Total Asset Turnover Ratios on Equity Returns: Dynamic Panel Data Analyses

2020 ◽  
Vol 27 (1) ◽  
pp. 19
Author(s):  
Jeanne-Claire Patin ◽  
Matiur Rahman ◽  
Muhammad Mustafa
Keyword(s):  
Stock Returns ◽  
Stock Prices ◽  
Generalized Method Of Moments ◽  
Ordinary Least Squares ◽  
Total Asset ◽  
Operating Efficiency ◽  
Positive Effects ◽  
Short Run ◽  
Asset Turnover ◽  
The Impact

This paper is an empirical exploration of the impact of total asset turnover ratios on stock returns of 1961 US public firms in different types of industries from 2001 to 2015. Stock prices are significantly influenced by operating performance of a company in efficiently utilizing its assets. For that matter, operating efficiency (as measured by total asset turnover ratio) plays a role in portfolio investment decisions. Pedroni’s heterogeneous panel co-integration procedures, associated bivariate error-correction model (ECM), dynamic ordinary least squares (DOLS) and generalized method of moments (GMM) are applied. Both stock returns and total asset turnover ratios in levels are nonstationary with I (1) behavior. Subsequently, both variables are found cointegrated. The panel ECM estimates suggest convergence of variables toward long-run equilibrium at moderate pace with short-run interactive positive feedback effects. Again, both DOLS and GMM estimates reveal short-run contemporaneous positive effects of total asset turnover ratios on stock returns in levels. In view of the findings of this study, firms should strive to improve operating efficiency, among others, to enhance competitiveness and thereby to boost their stock prices for rewarding shareholders. 

Determining total CEO compensation of selected US public companies

2018 ◽  
Vol 14 (2) ◽  
pp. 170-187 ◽  
Author(s):  
Matiur Rahman ◽  
Muhammad Mustafa
Keyword(s):  
Ceo Compensation ◽  
Generalized Method Of Moments ◽  
Panel Cointegration ◽  
Ordinary Least Squares ◽  
Data Set ◽  
Public Companies ◽  
Content Type ◽  
Positive Effects ◽  
Short Run ◽  
New Variables

Purpose The purpose of this paper is to explore the effects of total assets, stock performances, CEOs’ tenures, ages, and board sizes on total CEO compensations of 249 publicly listed US companies over a nine-year period from 2004-2012. Design/methodology/approach Pedroni’s panel cointegration, generalized method of moments, and dynamic ordinary least squares methodologies are applied. Findings All variables are non-stationary in log-levels. The findings show significant positive effects of total assets and stock performances on total CEO compensations. The effects of CEO’s tenure and age as well as board size on total CEO compensation deem negative. However, short-run net interactive feedback effects are generally positive with some exceptions. Research limitations/implications The above variables matter in rewarding the CEOs. They should be carefully weighed in for proper formulation of CEO compensation policy. Originality/value This paper applies relatively new econometric tools for a large panel data set. This work considers some new variables for determining CEO compensation in USA. The findings are relatively new with empirical originality.

scholarly journals Analysis of the New Kuznets Relationship: Considering Emissions of Carbon, Methanol, and Nitrous Oxide Greenhouse Gases—Evidence from EU Countries

2021 ◽  
Vol 18 (6) ◽  
pp. 2907
Author(s):  
Mara Madaleno ◽  
Victor Moutinho
Keyword(s):  
Nitrous Oxide ◽  
Least Squares ◽  
Fixed Effects ◽  
Ghg Emissions ◽  
Ordinary Least Squares ◽  
Kuznets Curve ◽  
Ekc Hypothesis ◽  
Long Run ◽  
Short Run ◽  
The Eu

Decreased greenhouse gas emissions (GHG) are urgently needed in view of global health threat represented by climate change. The goal of this paper is to test the validity of the Environmental Kuznets Curve (EKC) hypothesis, considering less common measures of environmental burden. For that, four different estimations are done, one considering total GHG emissions, and three more taking into account, individually, the three main GHG gases—carbon dioxide (CO2), nitrous oxide (N2O), and methane gas (CH4)—considering the oldest and most recent economies adhering to the EU27 (the EU 15 (Old Europe) and the EU 12 (New Europe)) separately. Using panel dynamic fixed effects (DFE), dynamic ordinary least squares (DOLS), and fully modified ordinary least squares (FMOLS) techniques, we validate the existence of a U-shaped relationship for all emission proxies considered, and groups of countries in the short-run. Some evidence of this effect also exists in the long-run. However, we were only able to validate the EKC hypothesis for the short-run in EU 12 under DOLS and the short and long-run using FMOLS. Confirmed is the fact that results are sensitive to models and measures adopted. Externalization of problems globally takes a longer period for national policies to correct, turning global measures harder and local environmental proxies more suitable to deeply explore the EKC hypothesis.

scholarly journals Do changes in income, deprivation, labour force status and family status influence smoking behaviour over the short run? Panel study of 15 000 adults

2013 ◽  
Vol 23 (e2) ◽  
pp. e106-e113 ◽  
Author(s):  
Tony Blakely ◽  
Frederieke S van der Deen ◽  
Alistair Woodward ◽  
Ichiro Kawachi ◽  
Kristie Carter
Keyword(s):  
Labour Force ◽  
Panel Study ◽  
Smoking Behaviour ◽  
Family Status ◽  
Labour Force Status ◽  
Short Run

REDUNDANCY OF MOMENT CONDITIONS AND THE EFFICIENCY OF OLS IN SUR MODELS

2008 ◽  
Vol 24 (5) ◽  
pp. 1456-1460 ◽  
Author(s):  
Hailong Qian
Keyword(s):  
Least Squares ◽  
Asymptotic Efficiency ◽  
Generalized Method Of Moments ◽  
Sufficient Conditions ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
American Statistical Association ◽  
Orthogonality Condition ◽  
Moment Conditions ◽  
Necessary And Sufficient

In this note, based on the generalized method of moments (GMM) interpretation of the usual ordinary least squares (OLS) and feasible generalized least squares (FGLS) estimators of seemingly unrelated regressions (SUR) models, we show that the OLS estimator is asymptotically as efficient as the FGLS estimator if and only if the cross-equation orthogonality condition is redundant given the within-equation orthogonality condition. Using the condition for redundancy of moment conditions of Breusch, Qian, Schmidt, and Wyhowski (1999, Journal of Econometrics 99, 89–111), we then derive the necessary and sufficient condition for the equal asymptotic efficiency of the OLS and FGLS estimators of SUR models. We also provide several useful sufficient conditions for the equal asymptotic efficiency of OLS and FGLS estimators that can be interpreted as various mixings of the two famous sufficient conditions of Zellner (1962, Journal of the American Statistical Association 57, 348–368).

scholarly journals Influence of Fiscal Policies and Labor Market Characteristics on Sustainable Social Insurance Budgets—Empirical Evidence from Central and Eastern European Countries

2021 ◽  
Vol 13 (11) ◽  
pp. 6197
Author(s):  
Adriana Florina Popa ◽  
Stefania Amalia Jimon ◽  
Delia David ◽  
Daniela Nicoleta Sahlian
Keyword(s):  
Labor Market ◽  
Social Insurance ◽  
Social Protection ◽  
Least Squares Method ◽  
Panel Study ◽  
Ordinary Least Squares ◽  
Political Agenda ◽  
Fiscal Policies ◽  
Protection Systems ◽  
Social Protection Systems

Social protection systems are a key factor for ensuring the long-term sustainability and stability of economies in the European Union, their reform being nowadays present in the political agenda of member states. Aging and the dependence on mandatory levies applied to the employed population on the labor market represent a threat for the sustainability of public social protection systems. In terms of sustainability, our purpose was to highlight the factors influencing social insurance budgets, considering the fiscal policies implemented in six countries of Central and Eastern Europe and their particular labor market characteristics. Therefore, a panel study based on a regression model using the Ordinary Least Squares method (OLS) with cross section random effects was used to determine the correlations between funding sources and labor market specific indicators. The data analyzed led to relevant results that emphasize the dependence of social insurance budgets on positive factors such as the average level of salaries, the share of compulsory social contributions, the unemployment rate, and the human development index, suggesting the continuing need for professional and personal development of the workforce.

Exploring the nonlinear effect of size on profitability: evidence from an insurance brokerage industry in an emerging market

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Richard Angelous Kotey ◽  
Richard Akomatey ◽  
Baah Aye Kusi
Keyword(s):  
Nonlinear Effect ◽  
Emerging Market ◽  
Empirical Studies ◽  
Random Effect ◽  
Generalized Method Of Moments ◽  
Ordinary Least Squares ◽  
Growth Strategies ◽  
Content Type ◽  
And Performance ◽  
Brokerage Firms

PurposeThis study examines the possible nonlinear effect of size on stakeholder and shareholder profitability in the Ghanaian insurance brokerage industry.Design/methodology/approachThis study employs a panel dataset of 64 Ghanaian insurance brokerage firms spanning 2011–2015. Static [ordinary least squares (OLS), fixed effect and random effect and dynamic (two-step generalized method of moments (GMM))] estimation techniques are employed to analyze the data.FindingsThe study finds the existence of both economies and diseconomies of scale and scope theories in the Ghanaian insurance brokerage industry confirming the existence of nonlinear nexus between size and performance. This finding is consistent for both stakeholder and shareholder profit performance. Thus, the results show that size improves profitability of insurance brokerage firms, but beyond a certain threshold, the relationship turns negative as size negatively affects profitability.Practical implicationsThe research findings have implications for both policy and research; the study recommends that Ghanaian brokerage managers should understand that not all growth is good and exercise a duty of care when applying growth strategies by monitoring size effect on performance so as not to go beyond the inflection point. Further research can be done to examine this effect in other contexts, timeframes and jurisdictions.Originality/valueThis research is unique in that it employs a panel dataset consisting of 96% of insurance brokerage firms in Ghana whilst employing both static and nonstatic regression models to examine the effect of size. The research analysis adopted is robust, and the findings are significant. Also, the lack of empirical studies on the operations and dealings of auxiliary institutions such as the insurance brokerage firms adds value to this research.

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