Specification Of Econometric Models Research Articles

The Student Evaluation of Teaching Premium for Clinical Faculty in Economics

This article uses student evaluation of teaching (SET) data for 947 faculty members affiliated with 90 U.S. colleges and universities to study the presence of a teaching quality rating premium for clinical economics faculty relative to traditional tenure-track economics faculty. Based on OLS estimation, we find this difference ranges between 3.9% and 4.8% and is robust to different econometric model specifications. Moreover, the average treatment effect from a propensity score weighting approach suggests that the difference ranges between 5.8% and 6.1%. Lastly, our analysis produces an institutional ranking of economics departments based on department-level SETs. Overall, our findings are encouraging signs for the hiring and retention of clinical faculty in economics departments.

The marginal cost of mortality risk reduction: Evidence from housing markets

We provide the first evidence on the rate at which spatial variation in all-cause mortality risk is capitalized into US housing prices. Using a hedonic framework, we recover the annual implicit cost of a 0.1 percentage-point reduction in mortality risk among older Americans and find that this cost is less than $3453 for a 67 year old and decreasing with age to less than $629 for an 87 year old. These estimates, while similar to estimates from the market for health care, are far below comparable estimates from markets for labor and automobiles, suggesting that the housing market provides an alternative, substantially cheaper channel for reducing mortality risk. We find this conclusion to be robust to a wide range of econometric model specifications, including accounting for associated expenditures on property taxes and the physical and financial costs of moving.

The crowding out of conventional electricity generation by renewable energy sources: implications from Greek, Hungarian, and Romanian electricity markets

To achieve ambitious energy-climate targets, all EU member states have introduced policies to support the market introduction of renewable energy sources (RES) generation. Motivated to close the gap of the merit order effect (MOE) in less mature Central and South East European electricity markets, we empirically confirm economic theory predictions that in the short run, an increase in RES generation reduces electricity prices. The merit order effect is initially econometrically confirmed and quantified. Different econometric model specifications are estimated to differentiate the MOE caused by wind and solar generation and to differentiate the MOE on high-load and low-load days. In addition, we simulate the adjustment of the realised day-ahead electricity prices to the no-RES generation scenario. Modern statistical methods are applied to bridge the gap in the limited public data availability to solve simulation models used in the power system or agent-based simulations. A family of data mining algorithms is applied for the merit order estimation used in the dynamic adaptation of the generation mix to the omitted RES generation. The estimated energy imbalance caused by the excluded RES generation is therefore compensated by the additional conventional generation dispatch according to the estimated power plant merit order. The estimated supply curves for each generation technology assist the reasoning behind the established MOE in econometric models. Based on our findings, policymakers should prioritise policies that facilitate the integration of RES into their electricity markets, which would in turn accelerate energy transition. With increasingly growing shares of renewables in the system, the governments need to rethink the support scheme, where the emphasis should be placed on efficiently integrating renewables in the power system by taking into account temporal and spatial dimensions.

Factors of the Regional Dynamics of the Newly Built Residential Area in Bulgaria for the 2005 – 2021 Period

Residential construction, as part of the construction sector, has developed quite dynamically over the last twenty years. This paper examines the dynamics of new housing construction over a seventeen-year period. The panel dataset includes household-related factors of demographic, social, and economic character regarding the demand for newly built housing estate. Different specifications of econometric panel models for the dynamics of new housing construction at district level in Bulgaria are built and estimated. The results show that the dependence of housing area of newly built dwellings by regions in Bulgaria is directly proportional to natural increase, migration, average annual wage, and number of pupils, and inversely proportional to unemployment. Interestingly, the variable “net enrollment rate of children in kindergartens” did not show the expected effect on the growth of newly built housing.

The equity–efficiency trade-off and the intensity of COVID-19 pandemic government responses: evidence from US states

ABSTRACT The relation between equity and efficiency remains at the heart of regional policy. This study captures the effect of the COVID-19 pandemic government responses on the above-mentioned relation. To do so, we employ cross-sectional data from US states for 2020 and a spatial econometric model specification in the context of Corona policy effects. We find an inverted-‘U’ relationship between inequality and efficiency. Additionally, the effect of the intensity of government responses to COVID-19 on the equity–efficiency relation depends on the state’s per capita gross domestic product (GDP) levels.

Welcome on Board? Appointment Dynamics of Women as Directors

Increasing the participation of women in top-level corporate boards is high on the agenda of policy-makers. Yet, we know little about director appointment dynamics and the drivers and impediments of women appointments. This study builds on organizational and group-level behavior theories and empirically investigates how ex-ante board structures and gender-specific board dynamics impact the representation of women on corporate boards. We study boards of listed firms in Europe between 2002 and 2019 and find a declining appointment probability for every additional woman, i.e., the share of women already on the board negatively predicts the likelihood of additional women appointments. Further, we find evidence of a replacement effect, i.e., the likelihood of a woman being appointed as director is significantly larger when a woman, compared to when a man, leaves the board. We do not find spillover effects from non-executive to executive boards. These results are robust to econometric model specifications that address potential endogeneity concerns using matching and instrumental variables. Our results confirm that board director appointments are gender specific and suggest that demand-side factors such as explicit and implicit norms drive women appointments up to a certain threshold.

NATURAL GAS ENERGY CONSUMPTION-WEALTH NEXUS: UNVEILING A NON-QUANTITATIVE WELFARE MEASURE

This paper examined the type of relationship existing between wealth accumulation ( and /or human development), and natural gas energy consumption (NGC) in Nigeria using the Human Development Index (HDI1 and HDI2) as proxies for human development and wealth accumulation. We employed the theoretical pedestal of natural gas energy consumption-growth nexus in our empirical review, and econometric model specification, and in evaluating the resultant estimates of this relationship. Annual time series data for the selected indicators were extracted for several years. Our results indicated that in the long-run, natural gas energy consumption does not facilitate human development and wealth accumulation vice versa in Nigeria. Furthermore, our results suggest that natural gas energy is consumed or utilized in Nigeria for non-wealth accumulation and non-human development purposes. We recommend that gas energy should be consumed and/or redirected to a more purposeful wealth and human development facilitating consumption.
 Keywords: Natural Gas Energy, Growth, Nigeria, ARDL Bounds Tests.
 JEL Classification Code:C50,Q32,Q400,Q430

Definition of Regulatory Targets for Electricity Non-Technical Losses: Proposition of an Automatic Model-Selection Technique for Panel Data Regressions

Non-technical losses (NTLs) are one of the main problems that electricity distribution utilities face in developing regions such as Latin America, the Caribbean, sub-Saharan Africa, and South Asia. Particularly in Brazil, based on the socioeconomic and market variables concerning all the distribution utilities, the National Electric Energy Agency (ANEEL) has formulated several specifications of econometric models for panel data with random effects, all aimed at determining an index that reflects the difficulty of combating NTLs according to the intrinsic characteristics of each distribution area. Nevertheless, given the exhaustive search for combinations of explanatory variables and the complexity inherent to defining regulatory NTL targets, this process still requires the evaluation of many models through hypothesis and goodness-of-fit tests. In this regard, this article proposes an automatic model-selection technique for panel data regressions to better assist the Agency in establishing NTL regulatory targets for the distribution of utilities in this country. The proposed technique was applied to panel data containing annual observations from 62 Brazilian electricity distribution utilities from 2007 to 2017, thus generating 1,097,789 models associated with the regression types in the panel data. The main results are three selected models that showed more adherence to the actual capacity of Brazilian distribution utilities to reduce their NTLs.

Corruption-related disclosure in the banking industry: evidence from GIPSI countries

This paper empirically investigates corruption-related disclosure in the banking industry, aiming to shed light on the reasons why financial institutions disclose corruption-related information in their annual financial reports. Using a total sample of 88 banks from the GIPSI countries during the period 2011-2019, our results reveal that, on average, banks involved in corruption issues disclose less on corruption-related matters than banks not involved in any corruption scandal. Moreover, banks not involved in corruption cases disclose even more information after other banks’ corruption events become public. These basic relationships, however, are shaped by the characteristics of each particular country in terms of control of corruption and the specific regulation on non-traditional banking activities. Our results are robust to different specifications of econometric models, to alternative empirical methods accounting for potential reverse causality and sample selection concerns and to the inclusion of internal corporate governance mechanisms.

Sectoral Productivity – Allocation of FDI Nexus in Bulgaria after the 2008-2009 Global Crisis

Studies of foreign direct investment in Bulgarian economy have had a decades-long history since the beginning of the transition to a market economy. This subject was particularly topical in the early transition period, when foreign investments were expected to be a major driver of the recovery and renewal of Bulgarian economy. Thirty years later, the relevance of this topic has not diminished, given the extraordinary degree of globalization of the world business into which Bulgarian economy must successfully integrate. The main goal of the current study is to present preliminary results of a statistical analysis of the dependence of sectoral labor productivity on the level of foreign direct investment allocated to various sectors of Bulgarian economy. For this purpose, two basic specifications of econometric models are built, adapted for estimation using panel data for the 2008-2019 period. The models are estimated using annual data for the sectors defined in the framework of the International Standard Industrial Classification of economic activities (ISIC-2008). Statistically significant results are obtained on various effects of the sectoral allocation of FDI in Bulgarian economy.

Energy Consumption under Circular Economy Conditions in the EU Countries

Due to industrialization, urbanization, and rapid population increases, the worldwide energy demand is increasing daily. The need for energy meets limitations, and searching for new energy sources is crucial, particularly for European countries. Energy crises occur temporarily due to different circumstances and cause oil price fluctuations. The present study aims to identify circular economy (CE) determinants that conditionally increase/decrease energy use to remain sustainable. It focuses on the linkage between energy consumption and circular economy in the European Union (EU) member states. In the econometric panel model specifications, two alternative endogenous variables are considered, i.e., total energy consumption and energy consumption from renewable sources. The results demonstrate that the selected CE indicators decreased the former and increased the latter. The data covered the period from 2010–2019. The significance of this study relies upon identifying the current level of CE implementation in the EU countries in the context of reducing total energy consumption and increasing the share of energy from renewable sources.

How does the sectoral composition of FDI induce economic growth in developing countries? The key role of business regulations

The prior empirical outcomes on the FDI-growth relationship are vastly conflicting. The key possible reason for these conflicting findings is the use of aggregate FDI, while FDI impacts largely depend on the receiving sectors of the host country. This study empirically estimated the influence of sectoral FDI on the economic growth and the role of business regulations in influencing the FDI-growth connection of 85 developing countries, for the time 1996–2019 and applied 2SLS method. The outcomes indicate the significant contribution of sectoral FDI inflows to economic growth. In contrast, the interaction of regulations with sectoral FDI negatively impacted host countries’ economic growth. Furthermore, in low income countries, only agriculture and industry FDI have growth promoting effect, while manufacturing and services FDI are insignificant. Similarly, FDI inflows to all sectors positively affect middle income countries’ economic growth except services FDI. However, FDI inflows to all sectors enhance high income countries economic growth. The regulations’ interaction with all types of FDI adversely affects the economic growth across all income groups, except agriculture and services FDI in the case of low and high income countries, which are found insignificant. The outcomes are consistent by employing diverse econometric techniques and model specifications.

Natural gas resource utilization, environmental policy and green economic development: Empirical evidence from China

Exploring the relationship between natural gas resource utilization, environmental policy, and green economic growth will help developing countries enact practical environmental and resources policy. China declared a “war on pollution” in 2014 in response to the worsening environmental pollution (called the “Atmosphere Ten Articles (ATA)” policy). Using the ATA policy in a quasi-natural experimental framework and adopting the quasi-difference-in-difference (quasi-DID) method, this paper conducts an empirical study based on hand-collated panel data of prefecture-level cities. The main findings are concluded as follows: (1) The ATA policy has a significant and negative impact on the green economic efficiency in Chinese cities. Essentially, this negative impact is a result of the more significant inhibitory effect over the reduction effect. The estimates are robust to various model specifications. (2) Chinese cities witnessed an increasing reduction in the green economic efficiency over time after implementing the ATA policy. (3) Heterogeneity analysis suggests that the negative effect mainly occurs in regions with relatively low natural gas utilization density, and we did not find such evidence in regions with high natural gas utilization density. These estimates are robust to alternative econometric model specifications, measurement methods, and identification strategies. The findings can provide new insights to understand the relationship between environmental policy, resource utilization, and green economic development.

Valuing the Quality-of-Life Aged Care Consumers (QOL-ACC) Instrument for Quality Assessment and Economic Evaluation.

ObjectiveThis paper reports on the valuation of the classification system for the Quality-of-Life Aged Care Consumers (QOL-ACC) instrument using a discrete choice experiment (DCE) with duration with a large sample of older people receiving aged care services.MethodsA DCE with 160 choice sets of two quality-of-life state–survival duration combinations blocked into 20 survey versions, with eight choice sets in each version, was designed and administered through an on-line survey to older Australians receiving aged care services in home and via interviewer facilitation with older people in residential aged care settings. Model specifications investigating preferences with respect to survival duration and interactions between QOL-ACC dimension levels were estimated. Utility weights were developed, with estimated coefficients transformed to the 0 (being dead) to 1 (full health) scale to generate a value set suitable for application in quality assessment and for the calculation of quality-adjusted life-years for use in economic evaluation.ResultsIn total, 953 older people completed the choice experiment with valid responses. The estimation results from econometric model specifications indicated that utility increased with survival duration and decreased according to quality-of-life impairment levels. An Australian value set (range − 0.56 to 1.00) was generated for the calculation of utilities for all QOL-ACC states.ConclusionThe QOL-ACC is unique in its focus on measuring and valuing quality of life from the perspective of older people themselves, thereby ensuring that the preferences of aged care service users are the primary focus for quality assessment and economic evaluation.Supplementary InformationThe online version contains supplementary material available at 10.1007/s40273-022-01158-2.

Expansive or focused attention? An exploration–exploitation perspective on e‐Business systems and firm performance

This study posits that executive attention can significantly influence the impacts of customer‐facing electronic business (e‐Business) systems on firm performance. Using the exploration–exploitation perspective (EEP) as an overarching theoretical framework, and the theoretical lens of attention‐based view (ABV), we develop an integrated model to provide insights into the impacts of customer‐facing e‐Business systems on firm performance. We categorize the capabilities of customer‐facing e‐Business systems into e‐Transaction and e‐CRM (customer relationship management) capabilities as exploitation and exploration capabilities, respectively. Further, following ABV, we conceptualize focused and expansive attentions as two different types of executive attention that also incorporate exploitation and exploration orientations. We hypothesize e‐Transaction and e‐CRM capabilities to have nuanced interactive effects with focused and expansive attention on firm performance measured using return on sales and Tobin's Q. We use a panel dataset with 484 firm‐year observations from 180 firms to test our hypotheses. We estimate our models using a two‐step generalized method of moments (GMM) approach to address issues relating to endogeneity, heteroskedasticity, and serial correlation, and to produce efficient estimates. The results provide broad support for the hypotheses and are robust to the alternative measurement of dependent variables, alternative econometric model specification, and potential endogeneity from omitted covariates. The integrated model developed and empirically validated in this study serves to provide a deeper understanding of the impacts of customer‐facing e‐Business systems on firm performance. The study also highlights the need for dual attention processes on the part of senior executives to fully realize the benefits offered by these systems.

Factors Affecting Taxpayers’ Adoption for Electronic Tax Register Machine (Etrms): The Case of Benshangul Gumuz Regional State Revenue Authority Taxpayers

The main objective of this study was examined the factors that affect taxpayers’ adoption for electronic tax register machine (ETRMs) the case of Benishangul Gumuz Regional State revenue authority taxpayers. Specifically, the study empirically examined the factor of perceived usefulness, perceived risk, subjective norms, self-efficiency and timeliness on the adoption of electronics register machine of taxpayers. This study adopted explanatory research design with arrangement of primary method of data collection via questionnaires, cross-sectional, quantitative approach. The sample of this study was taken 400 taxpayers from the total population of taxpayers 2,288. Descriptive and regression analysis were performed to analyze the data using Stata version 12. Besides, econometric model estimation procedures and specification tests plus multiple regression assumptions were tested. The estimation result of the marginal effect of the probit model for the factors of taxpayers’ adoption for e-tax register machine were four variables found to be significant on the probability of adoption for electronic tax register machine. The variables that become statistically significant include: perceived usefulness, perceived risk, self-efficiency and timeliness. However, subjective norms has positive but statistically insignificant relationship with adoption of electronic tax register machine. Therefore, in the case of Benishangul-Gumuz regional state taxpayer, subjective norm have not considered as a factor that affect adoption of electronic tax register machine. Keywords: Adoption, Electronic Tax register Machine, Benishanul-Gumuze Regional State Taxpayers. DOI: 10.7176/RJFA/13-3-01 Publication date: February 28 th 2022

Forecasting upon a star: Forecasting or wishful thinking?

The purpose of this paper was to perform a detailed analysis of the challenges faced while developing and using econometric models to forecast future transportation demand. To this end, a comparative analysis of the state of practice and state of the art was undertaken on a concrete example – Viracopos Airport in Brazil. A review of relevant technical and scientific literature identified a number of approaches and each representative example was synthesized into a specification “template”. We then compared the performance of each “template” with the observed demand, through an intra-series forecast. A general finding was that econometric model specifications proved to be somewhat homogenous and simpler in nature, with results indicating a relatively small difference in fit and forecast capability across models. Even with the elimination of what is typically considered the main culprit for deviations – the forecast uncertainty of the explanatory (input) variables – the forecast is still subject to sizeable deviation. To address this issue, we proposed developing some sanity check indexes, particularly relevant for long-term forecasts. We conclude that the challenges faced at the Viracopos Airport Concession were far from econometric ones, that the success of the demand forecast and the concession itself required more than a well estimated econometric model. Finally, regarding investment obligations within the concession agreement, we strongly recommend making them conditional to meeting demand milestones, given the inherent unpredictability in forecasts.

Does renewable energy substitute LNG international trade in the energy transition?

Abstract Renewable energy is a vital tool for the energy transition and sustainable development goals. The global economy, however, remains heavily reliant on fossil fuels despite efforts to reduce global greenhouse gas emissions. Demand for natural gas is rising as a bridge for moving towards a low-carbon economy, but whether natural gas and renewable energy represent substitutes in the global energy mix remains underexplored. We tackle this concern by examining the impact of renewable policies on international trade in liquified natural gas (LNG) among 1359 trading partners during the period 1988–2017. We measure renewable energy policies based on the ratio of renewable energy to total energy usage in importing trading partners, which also corresponds to a proxy for energy transition policies. The analysis is conducted using a global panel dataset in a trade gravity framework by applying various econometric methods and model specifications to measure LNG trade as a dependent variable. The results show that the energy transition, measured by the share of renewable energy, has a negative impact on LNG trade. This suggests that investing in cleaner energy technologies can reduce LNG trade globally, as a channel towards reducing natural gas demand. The results are consistent with the narrative where natural gas and renewable energy represent partial substitutes at the global level. However, subgroup analysis suggests that less-developed economies and the shale revolution period seem to impede progress towards the energy transition.

Economic Growth Patterns: Spatial Econometric Analysis for Russian Regions

In this article, we analyze the σ - and β -convergence, using the data of the socio-economic development of Russian areas, and discover the role of spatial autocorrelation in regional economic development. We are considering 80 areas of the Russian Federation for the period of 2010–2017. Moran coefficients were used to estimate spatial autocorrelation. We compare the Moran scatterplots for GDP per capita and GDP growth rates per capita in 2017 and in 2014. We study the impact on raising investment in leading capital and the costs of technological innovation. We evaluate a wide range of specifications of spatial econometric models for all kinds of weight matrices. We combine standard geographical proximity with specialization proximity to assess whether they are substitutes or additions to converging economic growth rates. The weight matrix of the neighborhood and specialization similarities are used. The weight matrix of specialization similarities of the regional economies is based on data on the structure of tax payments in 82 industries. The specialization structure of the region’s economy is related to its location. Clusters obtained by matrices of specialization proximity are well separable from each other in space. The connectivity within clusters and the boundaries between them become more apparent over time. It is shown that according to the results of estimation of conditional β -convergence models, the models of 2010–2014 and 2014–2017 differ significantly. There is a statistically significant β -convergence for the period 2010–2014. There is also the presence of spatial autocorrelation. Based on the results of valuation models constructed from data after 2014, it can be concluded that the coefficient estimates for the explanatory variables are not significantly different from zero, and accordingly there is no tendency towards regional convergence in terms of economic development. The results obtained in the work are stable for the proposed models and spatial weight matrices. Territorial proximity is a more important factor than the similarity of specialization for explanation the economic growth rates of Russian regions.

Corruption-Related Disclosure in the Banking Industry: Evidence From GIPSI Countries

This paper empirically investigates corruption-related disclosure in the banking industry, aiming to identify the most relevant theories which explain why financial institutions disclose corruption-related information to the public in their annual financial reports.Using a total sample of 88 banks from the GIPSI countries during the period 2011-2019, our results reveal that, on average, banks involved in corruption issues disclose less on corruption-related information than banks not involved in any corruption scandal. Moreover, banks not involved in corruption cases disclose even more information after other banks’ corruption events become public. These basic relationships, however, are shaped by the characteristics of each particular country in terms of control of corruption and the specific regulation on non-traditional banking activities. Our results are robust to different specifications of econometric models, and to alternative empirical methods accounting for potential reverse causality and sample selection concerns.