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This study aims to investigate the influence and impact mechanism of capital tax incentives on firm innovation.

This study employs the difference-in-differences (DID) method, in conjunction with the exogenous impact of accelerated depreciation (AD) pilot policy. This study selects Chinese listed companies from 2010 to 2017 as the research sample.

Firstly, AD exerts a substantial positive effect on the quantity and quality of the innovation output of firms, and the positive impact results primarily from heightened investment in fixed assets, particularly, machinery and equipment. Secondly, the influence of the policy is pronounced in non-state-owned enterprises, mature enterprises, less capital-intensive enterprises and non-high-tech industries, which all exhibit strong innovation incentives. Lastly, the tax incentive policy significantly stimulates firm innovation in the short term, but its long-term impact on innovation incentives lacks statistical significance.

This study highlights the significance of capital tax incentives in facilitating the innovation process in firms.

In order to study whether college scholarships can be an effective tool in raising students’ performance in secondary school, we use one aspect of the Kalamazoo Promise that resembles a quasi-experiment. The surprise announcement of the scholarship created a large change in expected college tuition costs that varied across different groups of students based on past enrollment decisions. This variation is arguably exogenous to unobserved student characteristics. We estimate the effects of this change by a set of “difference-in-differences” regressions where we compare the change in student outcomes in secondary school across time for different student “length of enrollment” groups. We also control for student fixed effects. We find positive effects of the Kalamazoo Promise on Promise-eligible students large enough to be deemed important – about a 9 percent increase in the probability of earning any credits and one less suspension day per year. We also find large increases in GPA among African American students.

This paper aims to examine the long run impact of information and communication technology (ICT) on economic growth in the Sub Saharan African (SSA) region. The direct impact of ICTs use was examined for a 27-year period (1990-2014), before the Millennium Development Goals (MDGs) era (1990-1999) and during the MDGs era (2000-2014). Second and third objectives examined the nonlinear effect of ICT in the economic growth and their threshold values, respectively. The main growth enhancing transmission channels of ICT use were also looked at.

The study uses panel method technique of system generalist method of moment. The data period was collected from the years 1990-2014 from 45 SSA countries. The three main proxies of ICT are fixed telephone lines, mobile phone users and internet users per 100 inhabitants.

For the direct impact analysis, mobile phone and internet were found to have triggered economic growth. However, for nonlinear effect analysis, mass penetration of ICT proxies seems to slow economic growth. The threshold analysis showed a penetration rate threshold of 4.5 per cent for both mobile phone and internet, and 5 per cent for fixed telephone line before economic growth gets triggered. Finally, the results indicated that, except for financial development, human capital, institutional quality and domestic investment were the main growth enhancing transmission channels of ICTs use in the economy.

From a policy perspective, results suggest SSA region to open more doors for investment in technology to ensure sustainable development. Such policy has to focus on investment into main transmission channels of ICT, namely, human capital, institutional quality and domestic investment. The policymakers have to ensure that penetration of mobile phone, fixed telephone and internet is met by improvement in human capital, institutional quality and domestic investment. Moreover, to fully use the potential of ICT, improving the financial sector is highly recommended.

In SSA, studies that address the impact of ICT on economic growth was almost non-existent, especially on its nonlinear effect and main transmission channels. While few studies have examined the direct impact of ICT, this study extended the scope by including the main growth enhancing transmission channels and nonlinear effect of ICT on SSA economies using recent data.

Panel data-based demand forecasting models have been widely adopted in various industrial settings over the past few decades. Despite being a highly versatile and intuitive method, in the literature, there is a lack of comprehensive review examining the strengths, the weaknesses, and the industrial applications of panel data-based demand forecasting models. The purpose of this paper is to fill this gap by reviewing and exploring the features of various main stream panel data-based demand forecasting models. A novel process, in the form of a flowchart, which helps practitioners to select the right panel data models for real world industrial applications, is developed. Future research directions are proposed and discussed.

It is a review paper. A systematically searched and carefully selected number of panel data-based forecasting models are examined analytically. Their features are also explored and revealed.

This paper is the first one which reviews the analytical panel data models specifically for demand forecasting applications. A novel model selection process is developed to assist decision makers to select the right panel data models for their specific demand forecasting tasks. The strengths, weaknesses, and industrial applications of different panel data-based demand forecasting models are found. Future research agenda is proposed.

This review covers most commonly used and important panel data-based models for demand forecasting. However, some hybrid models, which combine the panel data-based models with other models, are not covered.

The reviewed panel data-based demand forecasting models are applicable in the real world. The proposed model selection flowchart is implementable in practice and it helps practitioners to select the right panel data-based models for the respective industrial applications.

This paper is the first one which reviews the analytical panel data models specifically for demand forecasting applications. It is original.

Hausman (1978) represented a tectonic shift in inference related to the specification of econometric models. The seminal insight that one could compare two models which were both consistent under the null spawned a test which was both simple and powerful. The so-called ‘Hausman test’ has been applied and extended theoretically in a variety of econometric domains. This paper discusses the basic Hausman test and its development within econometric panel data settings since its publication. We focus on the construction of the Hausman test in a variety of panel data settings, and in particular, the recent adaptation of the Hausman test to semiparametric and nonparametric panel data models. We present simulation experiments which show the value of the Hausman test in a nonparametric setting, focusing primarily on the consequences of parametric model misspecification for the Hausman test procedure. A formal application of the Hausman test is also given focusing on testing between fixed and random effects within a panel data model of gasoline demand.

The purpose of this paper is to estimate the impact of one productive development program (PROPYME) in a developing nation like Costa Rica. This program seeks to increase the capacity of small and medium-sized firms (SMEs) to innovate.

Impacts have been estimated assuming that beneficiary firms are trying to maximize their profits and that PROPYME aims to increase these firms productivity. The impacts were measured in terms of three result variables real average wages employment demand and the probability of exporting. A combination of fixed effects and propensity score matching techniques was used in estimations to correct for any selection bias. The authors worked with panel data companies treated and untreated for the period 2001-2011.

PROPYME’s beneficiaries performed better than other firms in terms of labor demand and their probability of exporting. In addition, the dose and the duration of the effects of the treatment (timing effects) are important.

The authors study the impact in ways that go beyond the average treatment effects on the treated (ATT) usually estimated in the existing literature. Specifically, the research focusses on the identification of the timing or dynamic effects (i.e. how long should we wait to see results?) and treatment intensity (dosage effects).

Se estima el impacto de un programa de desarrollo productivo (Propyme) en un país en vías de desarrollo como Costa Rica. El Propyme busca incrementar la capacidad innovadora de las pequeñas y medidas empresas (pymes) costarricenses.

el impacto se ha estimado y evaluado asumiendo que las pymes beneficiaras buscan maximizar sus beneficios y que Propyme se enfoca en incrementar la productividad de esas empresas. El impacto se valoró en función de tres variables: salarios reales medios, empleo demandado y la probabilidad de exportar. Se utilizó una combinación de técnicas de efectos fijos y emparejamiento en las estimaciones con el fin de prevenir sesgos de selección. Se trabajó con un panel de datos, incluyendo empresas tratadas (beneficiarias de Propyme) así como no tratadas para el periodo 2001-2011.

los beneficiarios de Propyme tuvieron mejor desempeño que las restantes empresas en términos de empleo demandado y su posibilidad de exportar. Adicionalmente los efectos dinámicos (dosis y duración) de los tratamientos son importantes.

este artículo evalúa el impacto de una forma que va más allá de lo usual en la literatura por medio de los efectos promedios de los tratamientos sobre los beneficiarios. Esto por cuanto se enfoca en efectos dinámicos como la duración así como la intensidad.

The purpose of this paper is to explore the relationship between the ratification of the United Nations’ (UN’s) Convention on the Elimination of All Forms of Discrimination against Women (CEDAW) and women’s and girls’ health outcomes using a unique longitudinal data set of 192 UN-member countries that encompasses the years from 1980 to 2011.

The authors focus on the impact of CEDAW ratification, number of reports submitted after ratification, years passed since ratification, and the dynamic impact of CEDAW ratification by utilizing ordinary least squares (OLS) and panel fixed effects methods. The study investigates the following women’s and girls’ health outcomes: total fertility rate, adolescent fertility rate, infant mortality rate, maternal mortality ratio, neonatal mortality rate, female life expectancy at birth (FLEB), and female to male life expectancy at birth.

The OLS and panel country and year fixed effects models provide evidence that the impact of CEDAW ratification on women’s and girls’ health outcomes varies by global regions. While the authors find no significant gains in health outcomes in European and North-American countries, the countries in the Northern Africa, sub-Saharan Africa, Southern Africa, Caribbean and Central America, South America, Middle-East, Eastern Asia, and Oceania regions experienced the biggest gains from CEDAW ratification, exhibiting reductions in total fertility, adolescent fertility, infant mortality, maternal mortality, and neonatal mortality while also showing improvements in FLEB. The results provide evidence that both early commitment to CEDAW as measured by the total number of years of engagement after the UN’s 1980 ratification and the timely submission of mandatory CEDAW reports have positive impacts on women’ and girls’ health outcomes. Several sensitivity tests confirm the robustness of main findings.

This study is the first comprehensive attempt to explore the multifaceted relationships between CEDAW ratification and female health outcomes. The study significantly expands on the methods of earlier research and presents novel methods and findings on the relationship between CEDAW ratification and women’s health outcomes. The findings suggest that the impact of CEDAW ratification significantly depends on the country’s region. Furthermore, stronger engagement with CEDAW (as indicated by the total number of years following country ratification) and the submission of the required CEDAW reports (as outlined in the Convention’s guidelines) have positive impacts on women’s and girls’ health outcomes.

This study investigates how enhancing information and communication technology (ICT) affects female economic participation in sub-Saharan African nations.

Three female economic participation indicators are used, namely female labour force participation, female unemployment and female employment rates. The engaged ICT variables are fixed broadband subscriptions, mobile phone penetration and Internet penetration. The Generalized Method of Moments is used for the empirical analysis.

The following main findings are established: First, there is a (1) negative net effect in the relevance of fixed broadband subscriptions in female labour force participation and female unemployment and (2) positive net effects from the importance of fixed broadband subscriptions on the female employment rate. Secondly, an extended analysis is used to establish thresholds at which the undesirable net negative effect on female labour force participation can be avoided. From the corresponding findings, a fixed broadband subscription rate of 9.187 per 100 people is necessary to completely dampen the established net negative effect. Hence, the established threshold is the critical mass necessary for the enhancement of fixed broadband subscriptions to induce an overall positive net effect on the female labour force participation rate.

This study complements the extant literature by assessing how increasing penetration levels of ICT affect female economic inclusion and by extension, thresholds necessary for the promotion of ICT to increase female economic inclusion.

This chapter demonstrates that fixed-effects and first-differences models often understate the effect of interest because of the variation used to identify the model. In particular, the within-unit time-series variation often reflects transitory fluctuations that have little effect on behavioral outcomes. The data in effect suffer from measurement error, as a portion of the variation in the independent variable has no effect on the dependent variable. Two empirical examples are presented: one on the relationship between AFDC and fertility and the other on the relationship between local economic conditions and AFDC expenditures.