Endogenous Regressors Research Articles

ON GMM INFERENCE: PARTIAL IDENTIFICATION, IDENTIFICATION STRENGTH, AND NONSTANDARD ASYMPTOTICS

This paper analyses aspects of generalized method of moments (GMM) inference in moment equality models in settings where standard regularity conditions may break down. Explicit analytic formulations for the asymptotic distributions of estimable functions of the GMM estimator and statistics based on the GMM criterion function are derived under relatively mild assumptions. The moment Jacobian is allowed to be rank deficient, so first order identification may fail, the values of the Jacobian singular values are not constrained, thereby allowing for varying levels of identification strength, the long-run variance of the moment conditions can be singular, and the GMM criterion function weighting matrix may also be chosen sub-optimally. The large-sample properties are derived without imposing a specific structure on the functional form of the moment conditions. Closed-form expressions for the distributions are presented that can be evaluated using standard software without recourse to bootstrap or simulation methods. The practical operation of the results is illustrated via examples involving instrumental variables estimation of a structural equation with endogenous regressors and a common CH features model.

Inclusive bank based financial development in countries with special needs: A semiparametric analysis

What is the role of bank based financial development in inclusive sustainable development? Our paper tries to answer this question with a novel methodology that provides an estimate of the inequality-finance relationship for every country-year observation, allowing us to examine the distribution of the relationship of interest for various country groups. Unlike other papers in the literature, our estimates are free of both functional form mis-specification bias as well as bias from endogenous regressors. Our results indicate that financial development lowers income inequality in low income countries and countries that invest in primary education. This inequality-finance relationship is also sensitive to a country’s size of financial sector and quality of institutions. Our findings should be of particular interest to scholars and domestic policy makers of Countries with Special Needs, who face unique challenges meeting the goals set by United Nation’s 2030 Agenda for Sustainable Development.

Working from home and job satisfaction: evidence from Russia

PurposeThis study aims to investigate the impact of working from home and its duration on job satisfaction.Design/methodology/approachThe analysis was conducted on a representative panel data set from the Russian Longitudinal Monitoring Survey - Higher School of Economics (RLMS-HSE) for 2016–2021 using endogenous regression models. The impact of working from home on job satisfaction before and during the coronavirus disease 2019 (COVID-19) pandemic, and separately for men and women, was analysed.FindingsWorking from home was found to positively affect job satisfaction in the Russian labour market. From 2016 to 2021, men and women who worked from home were more satisfied with their jobs than their counterparts who did not work from home. The positive impact of working from home on job satisfaction was observed before and during the COVID-19 pandemic. However, remote workers (RWR) putting in more than eight hours per day reported lower job satisfaction.Research limitations/implicationsWorking from home can be considered as a measure to combat unemployment, increase employment and improve the utilisation (distribution) of human resources. Further research is required to analyse the impact of health issues and the need to care for young children or infirm persons on job satisfaction in remote work. A more detailed analysis is required of the factors that affect the job satisfaction of women who work remotely.Practical implicationsTo ensure that labour productivity increases and not decreases, employers are advised to develop more detailed working arrangements and labour management for RWRs. Especially for such assigned workers, task control regulations must be developed. To increase the motivation of individuals to work remotely, overtime should be paid at a higher rate.Social implicationsUnclear working time regulations lead to overwork, irregular working hours and burnout. For RWRs, this leads to lower job satisfaction and a consequent drop in productivity.Originality/valueThe empirical investigation is based on a representative panel of Russian data with six waves. Wide ranges of job characteristics were incorporated as determinants. The problem of causality was investigated. For models with an endogenous regressor, instrumental variables were tested and selected.

Which Way to Go Now? Financing Economic Growth in the Sustainable Development Era

Our paper uses a novel methodology to reexamine the relationship between financial development and economic growth in the era of sustainable development. Our empirical procedure deals with both functional-form misspecification bias as well as bias from endogenous regressors. It also provides an estimate of the growth-finance relationship for every country-year observation, allowing us to examine the relationship of interest for various country groups, using a global sample of 133 countries during 1960–2015. Our results indicate that countries with weak institutions and a smaller-than-average banking sector will reap more benefits from bank-based financial systems. The impact of financial development on economic performance has enormous policy implications for international institutions that provide policy support to countries in their pursuit of achieving the 2030 Agenda for Sustainable Development.

Financial dualism: An analysis of the effects of informal finance on formal finance in West African Economic and Monetary Union (WAEMU) countries

AbstractThis paper analyzes the effects of informal finance on formal finance in West African Economic and Monetary Union (WAEMU) countries. To this end, it uses a Probit model with a binary endogenous regressor and data from the Global Findex database, 2021. The findings indicate that having already saved informally positively affects the behavior of individuals to save formally. They also indicate that informal financial credit positively affects formal financial credits in the WAEMU. These findings indicate that formal finance is complementary to informal finance in the WAEMU. On the other hand, the findings show that labour force participation, mobile banking use and online banking use increase the likelihood of use of formal and informal services in the WAEMU. This paper suggests that formal financial institutions (mainly banks and microfinance institutions) should strengthen their collaboration with actors (money keepers, itinerant bankers, tontines systems) involved in the provision of informal financial services to populations in order to improve formal financial intermediation in the WAEMU.

Poverty, population growth and agglomeration effects in all Brazil cities

PurposeThis paper aims to test three hypotheses in city growth literature documenting the poverty reduction observed in Brazil and exploring a rich spatial dataset for 5,564 Brazilian cities observed between 1991 and 2010. The large sample and the author's improved econometric methods allows one to better understand and measure how important income growth is for poverty reduction, the patterns of agglomeration and population growth in all Brazilian cities.Design/methodology/approachThe author identifies literature gaps and use a sizeable spatial dataset for 5,564 Brazilian cities observed in 1991, 2000 and 2010 applying instrumental variables methods. The bias-corrected accelerated bootstrap percentile interval supports the author's point estimates.FindingsThis manuscript finds that Brazilian data for cities does not support Gibrat's law, raising the scope for urban planning and associated policies. Second, economic growth on a sustainable basis is still a vital source of poverty reduction (The author estimates the poverty elasticity at four percentage points). Lastly, agglomeration effects positively affect the city's productivity, while negative externalities underlie the city's development patterns.Originality/valueData for cities in Brazil possess unique characteristics such as spatial autocorrelation and endogeneity. Applying proper methods to find more reliable answers to the above three questions is a desirable procedure that must be encouraged. As the author points out in the manuscript, dealing with endogenous regressors in regional economics is still a developing matter that regional scientists could more generally apply to many regional issues.

Locationally Varying Production Technology and Productivity: The Case of Norwegian Farming

In this study, we leverage geographical coordinates and firm-level panel data to uncover variations in production across different locations. Our approach involves using a semiparametric proxy variable regression estimator, which allows us to define and estimate a customized production function for each firm and its corresponding location. By employing kernel methods, we estimate the nonparametric functions that determine the model’s parameters based on latitude and longitude. Furthermore, our model incorporates productivity components that consider various factors that influence production. Unlike spatially autoregressive-type production functions that assume a uniform technology across all locations, our approach estimates technology and productivity at both the firm and location levels, taking into account their specific characteristics. To handle endogenous regressors, we incorporate a proxy variable identification technique, distinguishing our method from geographically weighted semiparametric regressions. To investigate the heterogeneity in production technology and productivity among Norwegian grain farmers, we apply our model to a sample of farms using panel data spanning from 2001 to 2020. Through this analysis, we provide empirical evidence of regional variations in both technology and productivity among Norwegian grain farmers. Finally, we discuss the suitability of our approach for addressing the heterogeneity in this industry.

Synthesizing the role of technological innovation on sustainable development and climate action: Does governance play a role in sub-Saharan Africa?

The present study draws motivation from United Nation Sustainable Development Goals (UN-SDGs) and its impact by 2030. To this end, the current study explored the nexus between energy consumption (SDG-7), climate action (SDG-13), and economic growth (SDG-8) while controlling for role of government apparatus such as like voice of accountability, rule of law, control of corruption and technology innovation in a balanced panel of 46 Sub-Saharan African (SSA) economies from 1996 to 2020. For a robust study, the present study leverages on second-generation estimator such as cross-sectional SUR, two-stage least square (2SLS), 2SLS is referred to as the superior estimators to traditional pool OLS due to its capabilities of including endogenous regressors and efficiency. Empirical findings show that all the coefficients associated with mobile subscription (lnTI) are negative and statistically significant at 1% level of significance (P-value <0.01). This indicates that higher (lower) mobile cellular subscriptions results in the reduction (rise) of renewable energy consumption, implying that technological innovation in terms of the expansion of mobile cellular subscription hinders access to clean energy in SSA. Conclusively, the present study presents interesting outcomes concerning technology innovation, Governance, and SDGs goal 7 (clean energy) and 13 (climate action) in Sub-Saharan African blocs. Policy strategies are outlined in the concluding section.

Optimizing effects of firms’ technological and non-technological processes on export-led innovation

ABSTRACT This study contributes to research by evaluating the optimizing effects of innovation approaches on export-led innovation to ascertain a more efficient outcome. It uses the probit model with binary endogenous regressors to test the effects on 4,049 firms’ observations in Norway (1,784 manufacturing and 2,265 service firms). Results reveal that as export-led innovation induces a superior firm's innovation, it optimizes with innovation approaches – technological (STI) and non-technological (DUI) processes. While export-led innovation optimizes with STI in manufacturing firms’ product and process innovations, the optimizing effect is traceable to service firms’ process and service innovations. Nevertheless, export-led innovation optimizes with DUI in manufacturing firms’ service and New-to-Market innovations, and the effect only associates with service firms’ product innovations. Results show that while firms’ and export-led innovations optimize with the individual influence of STI and DUI, their interaction is inadequate. The study indicates that innovation methods are crucial for optimizing export-led innovation and present constructive policy implications that entrench invaluable decision-making that can enhance business performance.

Mean group instrumental variable estimation of time-varying large heterogeneous panels with endogenous regressors

The large heterogeneous panel data models are extended to the setting where the heterogenous coefficients are changing over time and the regressors are endogenous. Kernel-based non-parametric time-varying parameter instrumental variable mean group (TVP-IV-MG) estimator is proposed for the time-varying cross-sectional mean coefficients. The uniform consistency is shown and the pointwise asymptotic normality of the proposed estimator is derived. A data-driven bandwidth selection procedure is also proposed. The finite sample performance of the proposed estimator is investigated through a Monte Carlo study and an empirical application on multi-country Phillips curve with time-varying parameters.

A Spillover Effect of Human Capital on Gross Capital Formation: A Quantile Regression Approach

Abstract The major aim of this paper is to examine the extent to which human capital spillover effects are responsive to different quantiles of gross capital formation across selected 19 OECD countries for the period 1980-2017. We develop an endogenous model for estimating the spillover effects on investment regarding the bargaining power of workers. In this sense, different quantile regression models are applied to analyze this miscellaneous linkage and to correct possible diagnostic problems stemming from the endogenous regressors. The empirical results suggest that there are statistically significant spillover effects of human capital on investment level due to a change in the degree of threat option of capital and thereby a decrease in bargaining power of labor. Moreover, the findings reveal the fact that there is significant heterogeneity of human capital spillovers across different quantiles, which means that lowest quartile of investment activities are confronted with higher value of spillovers.

Trusting the Untrustworthy: An Exploration of Attitudes Towards the Populist Government in Poland Using Survey Data

The study explores attitudinal change in political trust, social trust and satisfaction with the Polish government over the years 2012–2016 using European Social Survey (ESS) data. To trace the attitudinal change, I used a probit model (contemporary measure) instrumenting political trust and satisfaction with governance as two endogenous regressors and created lags corresponding to years before and after the Law and Justice Party came to power. The key finding of the study is that voters dissatisfied with the government before the 2015 election campaign voted for the populist party, while the contemporary measure identified individuals with a higher degree of political trust and those sceptical towards their immediate social circle as supportive of the populist incumbent.

Do forecasts of bankruptcy cause bankruptcy? A machine learning sensitivity analysis

It is widely speculated that auditors’ public forecasts of bankruptcy are, at least in part, self-fulfilling prophecies in the sense that they actually cause bankruptcies that would not have otherwise occurred. This conjecture is hard to prove, however, because the strong association between bankruptcies and bankruptcy forecasts could simply indicate that auditors are skillful forecasters with unique access to highly predictive covariates. In this paper we investigate the causal effect of bankruptcy forecasts on bankruptcy using nonparametric sensitivity analysis. We contrast our analysis with two alternative approaches: a linear bivariate probit model with an endogenous regressor and a recently developed bound on risk ratios called E-values. Additionally, our machine learning approach incorporates a monotonicity constraint corresponding to the assumption that bankruptcy forecasts do not make bankruptcies less likely. Finally, a tree-based posterior summary of the treatment effect estimates allows us to explore which observable firm characteristics moderate the inducement effect.

Public assistance, survival, and household trust during the containment period of the first wave of the SARS-CoV-2 pandemic in Togo.

This paper analyzes the impact of public assistance during the first wave of the SARS-CoV-2 pandemic with regard to household survival, using data from a two-round survey of 1274 respondents in Togo conducted by the National Institute of Statistics, Economic and Demographic Studies. The analysis uses the propensity score matching method, the probit model, and the discrete endogenous regressor. The first result shows that more than two thirds of respondents experienced income shocks due to the health crisis. The second result shows that public assistance programs have enabled the beneficiary populations to overcome the impact of shocks.

Food security in Indonesia: the role of social capital

ABSTRACT Social capital (i.e. bonding and bridging) affects food security. In Indonesia, studies have been conducted at the site level, covering households in specific provinces, districts, subdistricts, or even villages. Accordingly, this study contributes to the existing literature by employing a sample of 68,304 households across Indonesia using data from Statistics Indonesia’s (BPS’s) 2018 National Socioeconomic Survey (SUSENAS). Based on Lewbel’s (2012. “Using Heteroscedasticity to Identify and Estimate Mismeasured and Endogenous Regressor Models.” Journal of Business and Economic Statistics 30 (1): 67–80) two-stage least squares (2SLS) regression test, the results suggest that bonding and bridging social capital positively affect food security. Specifically, bridging social capital has a more substantial influence on food security.

Mean Group Instrumental Variable Estimation of Time-varying Large Heterogeneous Panels With Endogenous Regressors

Mean Group Instrumental Variable Estimation of Time-varying Large Heterogeneous Panels With Endogenous Regressors

Monitoring cointegration in systems of cointegrating relationships

Monitoring statistics for structural changes in systems of cointegrating relationships are proposed. The approach is based on parameter estimation over a calibration period. In case of homogenous systems and cross-sectional independence the pooled fully modified OLS estimator takes into account the effects of error serial correlation and regressor endogeneity. Cross-sectional dependence is allowed by using the pooled fully modified GLS estimator for homogenous systems and the fully modified SUR estimator for inhomogenous systems. The detectors show decent behaviour under the null hypothesis with controlled rejection probabilities and power against two alternatives for different data generating processes. An empirical application investigates deviations from the arbitrage parity condition for exchange rate triplets including Bitcoin. The procedures detect breakpoints in May to August 2014 and in January to May 2015 indicating an instability in arbitrage parities. Following this, a promising portfolio trading strategy based on the breakdates is constructed.

The Relation between Corruption and Economy in OECD Countries: A Moderating Role of Tax Revenue

This research study's goal is to examine how tax income influences the relationship between corruption and the economy in OECD countries. OECD countries 35 panel data from the years 1996 to 2021 have been used for this purpose. Economic growth is used as the dependent variable, corruption and tax revenue as the independent variables, and education, foreign direct investment (FDI), inflation, and governance as the control factors. First, we used the cross-sectional dependence CD test to check whether the cross-correlations of the errors are zero. Next, Panel unit-root test is used to check whether the data are stationary. Hausman test is used test to check whether endogenous regressors (predictor variables) are present in the regression model. Finally, Panel ARDL (PMG) techniques used for short-run and long-run analysis of variables. Similarly, the Baron and Kenny estimating process has been used to assess the direct and indirect link between these variables to discover the mediating influence between corruption, tax revenue, and economic growth. According to the panel ARDL (PMG) analysis's findings, economic growth is long-term positively impact by corruption, tax revenue, education, FDI, and governance. While inflation and political unrest have a negative and considerable impact on economic growth. The study's main finding is that tax revenue and corruption have a positive and substantial relationship with economic growth. The principal-Agent theory aids in understanding both governmental structure and the effects of corruption. The mediation analysis's conclusion is that corruption not only directly affects economic growth, but also indirectly. The study provides policymakers with comprehensive knowledge that decreasing corruption results in higher tax receipts and economic growth.

Estimation and identification of latent group structures in panel data

This paper provides a framework for joint estimation and identification of latent group structures in panel data models using a pairwise fusion penalized approach. The latent structure of the model allows individuals to be classified into different groups where the number of groups and the group membership are unknown. The individuals within a group have common slope parameters, while parameter heterogeneity is allowed across the groups. A penalized least squares (PLS) approach is introduced for models with exogenous regressors. When the model contains endogenous regressors, a penalized generalized method of moment (PGMM) is introduced. To implement the proposed approach, an alternating direction method of multipliers algorithm has been developed. The proposed method is further illustrated by simulation studies which demonstrate the finite sample performance of the method, and is applied in an empirical analysis.

The Dynamics of Moonlighting in Pakistan

The study explores the dynamics of moonlighting, demographics, human capital and association of occupations between primary and secondary job. The paper is based on cross-section data Labour Force Survey 2006-07 and limited to male wage workers residing in urban areas. Among two motives according to theoretical framework of moonlighting; first, constraint on hours worked in first job and second is wage rate is lower than the reservation wage in the primary occupation; within limited information available on different variables our results are skewed toward first motive and earnings from the primary occupation are insignificant in moonlighting decision. The model specification also attempts to correct the endogenous regressor in probit estimation. Among moonlighters ‘Professionals’ and ‘Technicians’ are holding their secondary job in same occupational category; apart from these two occupational categories managers and elementary occupations also seems popular for moonlighting. JEL classification: J22, J24 Keywords: Moonlighting, Labour Mobility, Occupational Association