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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.

Foreign Direct Investment (FDI) is an important means of boosting the agricultural sectors of developing economies. The first necessary step to formulate effective public policies to encourage agricultural FDI inflow to a host country is to develop a comprehensive understanding of the main determinants of FDI inflow to the agricultural sector, which is the main objective of the present study.

In view of this, we take a comprehensive approach to exploring the macroeconomic and institutional determinants of FDI inflow to the agricultural sector by examining a large panel data set on agricultural FDI inflows of 37 countries, investigating both groups of developed and developing countries, incorporating a large list of potentially relevant macroeconomic and institutional variables, and applying panel-data econometric models and estimation structures, including pooled, fixed-effects and random-effects regression models.

The general pattern of our findings implies that the degree of openness of an economy has a negative effect on FDI inflows to agricultural sectors, suggesting that the higher the degree of openness in an economy, the lower the level of agricultural protection against foreign trade and imports, and thus the less incentive for FDI to inflow to the agricultural sector of the economy. Additionally, our results show that economic growth (as an indicator of the rate of market-size growth in the host economy) and per-capita real GDP (as an indicator of the standard of living in the host country) are both positively related to FDI inflows to agricultural sectors. Our other results suggest that agricultural FDI tends to flow more to developing countries in general and more to those with higher standards of living and income levels in particular.

FDI inflow has not received much attention with respect to the identification of its main determinants in the context of agricultural sectors. Additionally, there are very few panel-data studies on the determinants of FDI, and even more surprisingly, there are no such studies on the main determinants of FDI inflow to the agricultural sector. We have taken a comprehensive approach by studying FDI inflow variations across countries as well as over time.

The purpose of this study is to verify all factors that promote renewable energy (RE) consumption. Past studies have shown that financial development (FD) and economic growth (EG) are the major drivers toward RE development, while oil prices had mixed outcomes in different regions by different studies.

Global warming effects have been the major reason of the transition by nations from fossil fuel use to RE sources that are considered as friendly to the environment. This research uses the fixed effects and random effects techniques, to ascertain the factors which impact RE development. The generalized linear model is also used to check the robustness of the Fixed Effects and Random Effects models’ results, while the Kao, Pedroni and Westerlund tests are used to check cointegration in the specified model.

The major findings of this study show the importance of EG and FD in promoting RE development. Oil prices, inflation rate and public sector credit present a negative effect on RE development, while foreign direct investment does not significantly impact RE development.

This research recommends the use of FD in promoting RE sources, as well as the stabilization of oil prices and consumer prices.

This research is important because it specifies the three proxies of FD, together with foreign direct investment inflation rate, EG and oil prices, in modeling RE. By investigating the impact of oil prices on RE in the emerging seven economies, this research becomes one of the few studies done in this region, as per the authors’ knowhow.

Globalization occupies a central research activity and remains an increasingly controversial phenomenon in economics. This phenomenon corresponds to a subject that can be criticized through its impact on national economies. On the other hand, the world economy is evolving in a liberalized environment in which foreign direct investment plays a fundamental role in the economic development of each country. The advent of financial flows – FDI, remittances and official development assistance – can be a key factor in the development of the economy. The subject of this article is to analyses the effect of financial flows on economic growth in developing countries. Empirically, different approaches have been employed. As part of this work, an attempt was made to use a panel data approach. The results indicate ambiguous effects and confirm the results of previous work.

The authors seek to study the effect of foreign direct investment, remittances and official development assistance (ODA) and some control variables i.e. domestic credit, life expectancy, gross fixed capital formation (GFCF), inflation and three institutional factors on economic growth in developing countries by adopting the panel data methodology. Then, the authors will discuss empirical tests to assess the econometric relevance of the model specification before presenting the analysis of the results and their interpretations that lead to economic policy implications. As part of this work, the authors have rolled panel data for developing countries at an annual frequency during the period from 1990 to 2016. In a first stage of empirical analysis, the authors will carry out a technical study of the heterogeneity test of the individual fixed effects of the countries. This kind of analysis makes it possible to identify the problems retained in the specific choice of econometric modeling to be undertaken in the specificities of the panel data.

The empirical results validate the hypotheses put forward and indicate the evidence of an ambiguous effect of financial flows on economic growth. The empirical findings from this analysis suggest the use of economic-type solutions to resolve some of the shortcomings encountered in terms of unexpected effects. Governments in these countries should improve the business environment by establishing a framework that further encourages domestic and foreign investment.

In this article, the authors adopt the panel data to study the links between financial flows and economic growth. The authors considered four groups of countries by income.

The purpose of this paper is multifold. First, it is to investigate the relationship between social network sites (SNSs) usage and youth's school absenteeism. Second, it is to identify causal relationship between SNSs usage and absenteeism. Third, it is to explore whether SNSs usage causally affects youth's study–work choice after leaving high school. In addition to SNSs usage in general, abnormal SNSs usage is further discussed.

The Longitudinal Study of Australian Children (LSAC) data are utilised. Lagged variable analysis is used to alleviate reverse causality. Instrumental variable approach and the Lewbel method are used to identify causality. Random effects panel data approach (without and with IVs) is additionally applied to increase efficiency and account for individual-specific effects. Random effects approach allowing for within and between effects is applied, enabling us to control for fixed effects. The primary instrument is a dummy indicating whether a youth more often communicates with close friend electronically or face-to-face.

Using SNSs leads to significantly higher probability of a teenager being late for school, skipping class and having trouble not following school rules. The effect is more consistent regarding abnormal SNSs usage, compared to SNSs usage in general. Additionally, SNSs usage decreases the probability of a youth studying after 18 years old, even after controlling for absenteeism.

The findings in this paper highlight the importance of preventing youth (e.g. via enabling children-safe mode or setting up maximum daily access time) from overusing SNSs.

With the transition to hybrid (mixing remote and face-to-face) learning during and after COVID-19, online interactions are becoming inevitable in students' learning. The findings in this paper indicate that usage, especially abnormal usage, of SNSs increases the probability of absenteeism call for attention from stakeholders including teachers, parents and youth themselves.

This paper provides the first causal and longitudinal evidence linking SNSs usage to absenteeism and youth labor outcomes.

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.

The purpose of this study is to investigate the relationship between fiscal policy (tax revenues and government expenditure) and economic happiness. The panel data are used from 2012 to 2016 for 18 countries of the Middle East and North Africa (MENA) region.

The study adopted the Barro (1990) model of endogeneity growth to characterize the relationship between fiscal policy and economic happiness. The study estimated the model by using the pooled ordinary least squares method, the fixed effects method and the random-effects method. In addition, the study used the dynamic estimate of this relationship rather than the conventional static estimate through the generalized method of moments’ method. This leads to overcoming the endogeneity problem between the dependent variable and the independent variables.

The main findings indicated that there is a negative and statistically significant relationship between nondistortionary taxes and economic happiness. Also, there is no relationship between public expenditure and economic happiness, whether productive or nonproductive. The results confirmed a positive and significant relationship between other revenues and economic happiness. The current study recommended the diversification of other public revenue sources to increase its contribution to public expenditure financing and the restructuring of the tax system, particularly nondistortionary taxes. These taxes must be replaced by other revenues or by distortionary taxes to increase economic happiness.

The research represents a strong starting base that can help researchers to conduct more studies on economic happiness by using different measures and comparing their results to find out the determinants of happiness. The relationship between economic happiness and fiscal policy with its different aspects requires more studies, especially the relationship between taxes and economic happiness in our region. The study of the relationship between public expenditure and economic happiness according to economic activities can guide decision-makers to direct the expenditure toward economic activities that achieve the happiness of their citizens. Enriching this study requires the availability of fiscal data for the entire MENA region for longer periods, which allow us to divide the countries of the region into petroleum and nonpetroleum countries, but the scarcity of data is one of the limitations of the study.

The governments of MENA countries should diversify other public revenue sources to increase the financing public expenditure by the expense of tax revenues, especially nondistortionary taxes, which would increase the economic happiness of their citizens.

This study is one of the rare studies that investigate the relationship between fiscal policy and economic happiness at the global level. This study contributed to filling the gap of this issue in the MENA region and enriching global literature through the experience of the MENA region. Moreover, this study investigated all aspects of fiscal policy, in contrast to other studies that focused on one of its aspects. The weakness in these studies is because of the lack of correlation between the sources of revenues and the face of their spending.

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.

This study empirically examines the impact of rural roads on consumption of households in Ethiopia.

Both descriptive statistics and econometric techniques are used to address the aforementioned objective. Specifically, quantile regression, fixed- and random-effect models are used to understand the impact of rural road quality on welfare.

The econometric analysis revealed that improving the quality of rural roads and/or creating access to all-weather roads raises households' average real consumption per capita by as much as 10%. The other transport indicator – mode of transport – also has a positive effect on real consumption per capita. The result indicated that real consumption per capita for households using the traditional mode of transport would increase by as much as 7% compared to those using foot as a major mode of transport. However, the fixed quantile estimation result revealed that rural road access has a positive and significant effect on consumption per capita only for the 0.8th and 0.9th percentiles, indicating that the access to roads is not pro-poor.

Improving rural roads to a level of all-weather road standards and provision of agricultural transport facilities should be strategic priorities.

This study provides empirical evidence pertinent to the effect rural mobility has on the consumption of households as well as the pro-poorness of such investments in rural settings.

In recent decades, the use of capital punishment has declined, but in its place, a ‘new death penalty’ has arisen: life without parole (LWOP), which is being used far more frequently and for more crimes than capital punishment ever was. Yet, LWOP has received far less scholarly attention than the death penalty. Because of its greater scale, assessing the effects of LWOP on crime has important policy implications and is a better test of extreme penalties. Existing studies of LWOP focus on humanitarian issues and ignore its potentially reciprocal relationship with crime. Therefore, we use available LWOP data to fill these gaps in the literature, using models specifically designed to control for potential reciprocal effects. The results indicate there is no reciprocal causation between LWOP and violent crime and, at best, LWOP’s impact on crime is small, temporary, and, most importantly, no greater than the impact of life with parole.