Search results

This chapter revisits the Hausman (1978) test for panel data. It emphasizes that it is a general specification test and that rejection of the null signals misspecification and is not an endorsement of the fixed effects estimator as is done in practice. Non-rejection of the null provides support for the random effects estimator which is efficient under the null. The chapter offers practical tips on what to do in case the null is rejected including checking for endogeneity of the regressors, misspecified dynamics, and applying a nonparametric Hausman test, see Amini, Delgado, Henderson, and Parmeter (2012, chapter 16). Alternatively, for the fixed effects die hard, the chapter suggests testing the fixed effects restrictions before adopting this estimator. The chapter also recommends a pretest estimator that is based on an additional Hausman test based on the difference between the Hausman and Taylor estimator and the fixed effects estimator.

The authors propose to estimate a varying coefficient panel data model with different smoothing variables and fixed effects using a two-step approach. The pilot step estimates the varying coefficients by a series method. We then use the pilot estimates to perform a one-step backfitting through local linear kernel smoothing, which is shown to be oracle efficient in the sense of being asymptotically equivalent to the estimate knowing the other components of the varying coefficients. In both steps, the authors remove the fixed effects through properly constructed weights. The authors obtain the asymptotic properties of both the pilot and efficient estimators. The Monte Carlo simulations show that the proposed estimator performs well. The authors illustrate their applicability by estimating a varying coefficient production frontier using a panel data, without assuming distributions of the efficiency and error terms.

In recent years, the topic of women's entrepreneurship has gained increasing attention from researchers and policymakers. Its role in economic growth and development has been widely recognized in several studies. However, the relationship between gender in entrepreneurship and innovation is an underexplored aspect in particular at a country-level perspective. This paper aims to answer the following question: Does female entrepreneurship impact innovation at a national level?

Using a panel dataset of 35 Organization for Economic Co-operation and Development (OECD) member countries over the period 2002–2019, the authors carried out a comprehensive econometric analysis, based on the fixed-effect model, the random-effect model and the feasible generalized least squares estimator, as well as a battery of tests to prevent problems of multicollinearity, heteroscedasticity and autocorrelation of the error terms. In doing so, the authors found consistent and robust results on the linear and nonlinear relationship between women's entrepreneurship and innovation, using selected country indicators from the Global Entrepreneurship Monitor (GEM) consortium, the Worldwide Governance Indicators (WGI) and the World Development Indicators (WDI), including female self-employment, female nascent entrepreneurship and R&D investment and controlling for the same relationships in the case of men's entrepreneurship.

This study shows that the level of R&D investment, which according to the literature can be considered as a proxy of innovation, is higher when the level of women's entrepreneurship is low. However, exploring more in depth this relationship and the relationship between male entrepreneurship and innovation, the authors found two important and new results. The first one involves the different impact on R&D investment of female self-employment and female nascent entrepreneurship. In particular, female self-employment appears to have a linear negative impact on the R&D, while the impact of female nascent entrepreneurship is statistically nonsignificant. The second one affects the nonlinearity of the negative effect, suggesting that very different challenges are possible at different levels of women's entrepreneurship. In addition, analyzing the role of human capital in the relationship between R&D investment and women entrepreneurship, it emerges that higher education (as the main component of human capital) makes early-stage women's entrepreneurship more technologically consuming, which promotes R&D investment. A higher level of education lessens the significance of the negative relationship between the simplest type of women entrepreneurship (female self-employment) and R&D investment.

The originality of the study is that it provides new evidence regarding the link between women's entrepreneurship and innovation at the macro level, with a specific focus on self-employed women entrepreneurs and early-stage women entrepreneurship. In this sense, to the best of the authors' knowledge, this study is among the few showing a nonlinear relationship between women's entrepreneurship and country-level innovation and a negative impact only in the case of female self-employment. Moreover, this study has relevant implications from a policymaking perspective, in terms of promoting more productive women's entrepreneurship.

The paper investigates the prevalence of extreme poverty in a panel of 39 sub-Saharan African (SSA) countries over the period 2000–2018 while accounting for spillover effects.

The study adopts the recently developed spatial dependence-consistent, bias-corrected quasi-maximum likelihood (QML) estimators and the linear dynamic panel regression to control for the potential endogeneity in poverty and corruption spillovers.

The spatial model shows. consistently across all the specifications, that there is a substantial spillover effect of corruption and poverty across the region. Additionally, the study also found that investment in health and education is a significant determinant of poverty in the region. However, the effectiveness of these policy variables to reduce poverty declines in the face of corruption spillovers. More importantly, the empirical analysis shows that poverty does not only exhibit spatial spillovers but also has a persistent effect over time. The results, therefore, suggest that to reduce poverty in the region, sub-Saharan African governments must adopt spatially differentiated policies and programmes by working together to reduce unemployment and corruption in the region, and not the widely adopted spatially mute designs currently in place. The research and policy implications are discussed.

The study accounts for spatial dependency and spillover effects in the analysis of poverty and corruption in SSA

This study aims to investigate the relationships between loan growth, loan losses and net income after the 2008 global financial crisis. This study further conducts a comparative analysis by considering the period of COVID-19.

This study uses panel data models such as one-step system GMM, random effects, fixed effects and OLS, with a data set of 131 Chinese commercial banks from 2009 to 2020.

The study finds no significant relationship between loan growth and future loan losses. However, after adjusting loan loss by net interest income (NII-adjusted loan loss), the study reveals that loan growth in the subsequent year decreases if NII-adjusted loan loss increases. The study also demonstrates the positive effect of loan growth on net income as newly expanded loans are funded at similar costs but offered at a lower rate compared with existing loans. During COVID-19, loan growth and net income were higher than in previous years.

The findings suggest that Chinese banks can increase lending to support the economy without sacrificing loan quality, emphasizing the importance of maintaining and enhancing credit policies and practices. Chinese banks should also continue to refine their pricing strategies for loans and deposits. The findings also imply that China's policy responses to the impact of COVID-19 could serve as lessons for future policy decisions.

Today, the sustainability and outreach of microfinance institutions (MFIs) are crucial to the success of microfinance and the sector’s potential to make a lasting impact. The ability of MFIs to operate financially well without sacrificing their social goals has come under scrutiny. This study aims to identify the kind of relationships between the two objectives of MFIs in Ethiopia.

This study investigated the association between the outreach and financial sustainability of Ethiopian MFIs from the years 2012 to 2021 using a balanced set of panel data. The study used secondary data and employed a descriptive research design and a quantitative research approach. To this end, random and fixed effects estimation models, as well as three-stage least squares, with the model of seemingly unrelated regression (SUR) are used.

According to the study, outreach performance enables MFIs to achieve sustainability/financial performance. On the other side, MFI that are financially sound improve social performance. There was therefore no trade-off between the two objectives.

As Ethiopia’s microfinance sector shifts away from government and non-government backing and toward commercialization, such research is crucial. This aspect of the Ethiopian microfinance industry has gotten little consideration in research. The SUR model was used in the study together with random and fixed effect estimators, and the most reliable estimation result was chosen based on the necessary tests.

The theoretical debate of corruption's impact on economic growth remains unsettled, making it an empirical question. This study aims to investigate corruption's effect on BRICS countries' economic growth.

A panel dataset on BRICS countries spanning 1996 to 2020 was used. Bias-corrected estimators in small dynamic panels were employed to estimate a growth model as a linear-quadratic function of corruption that accounts for cross-sectional dependence, endogeneity and unobserved heterogeneity due to country and time-specific characteristics.

The results indicate that corruption is detrimental to economic growth in BRICS countries; the quadratic relationship implies corruption is less prevalent in some countries than others. Thus, governments of BRICS countries are encouraged to embark on anti-corruption policies to boost their economic performance.

An important limitation of corruption studies is the difficulty in measuring real corruption experiences due to the secretive nature of corruption and the fact that corruption is known not to leave a paper trail. For the uncertainty of the index estimates, the analysis used a continuous corruption composite score measuring the standard deviation of the extent to which public power is exercised for public gain. Furthermore, estimation and inference are robust to small dynamic panels with a general form of cross-sectional dependence.

Empirical studies regarding the impact of the real exchange rate (RER) on economic growth are extensively available. However, the literature as a whole appears to report varying results, while the causes of such differences have not been analyzed systematically. The present study aims to fill the gap in the literature.

In this paper, the authors compile 543 empirical estimates from 51 studies of the exchange rate-growth nexus in order to meta-analyze its relationship. Meta-analysis allows the authors to quantitatively synthesize previous empirical studies and explain the variation in the results. This method also enables us to investigate the possibility of publication bias, as there is a tendency in research only to report results that are both statistically significant and show the expected signs.

After addressing publication bias and heterogeneity in the estimates, the meta-regression results show that RER depreciation (or undervaluation) genuinely favors economic growth. On average, RER depreciation has a greater impact on economic growth in developing countries than the developed ones. The study’s results imply that maintaining an undervalued RER could be favorable to spur economic growth, especially in developing countries.

Initially predominant in the medical literature, meta-analysis has been on a rising edge in economics. This progress has produced many systematic quantitative review analyses with continuously improved statistical-econometric practices related to economic variables. However, to the authors’ knowledge, no comprehensive meta-regression analysis of the relationship between exchange rate and economic growth has been conducted and published in any publicly accessible academic outlet. Therefore, this study aims to fill this gap in the literature.

The purpose of this research is to examine Micro-, small- and medium-sized enterprises (MSMEs). Which have limited access to financial resources from financial intermediaries. Thus, resource allocation is a primary concern for them.

This research studies the determinants of cash conversion cycle components and cash flow of MSMEs operating in Ecuador. This study examined a robust sample of 19,680 firms from 2000 to 2020, using the two-step generalized methods of moments to control for endogeneity and multicollinearity of independent variables issues.

The sample was divided into working capital intensive and fixed capital intensive firms. It was found that in every segment (micro-, small- and medium-sized), the majority of firms are working capital intensive and their average return is higher. This implies that small business owners assign the majority of their resources to current assets, which thus far have enabled them to achieve higher profitability.

Research investigated Ecuadorian MSMEs in a dollarized developing environment. Scrutinizing working capital intensive vs fixed capital intensive.