Introduction

Klevmarken, N. Anders

doi:10.1016/0014-2921(89)90131-1

Cited by 87 publications

(20 citation statements)

References 7 publications

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“…For this estimation, we use panel data with a probit random effects model. First, we select panel data due their benefits listed in the literature (Hsiao, 1985(Hsiao, , 1986Kelvmarken, 1989;Solon, 1989;Baltagi, 2002;p.5) as controlling for individual heterogeneity or allowing for identification and measurement of effects that are simply not detectable in pure cross-section on pure time-series data, among others. Second, we use a random effects probit model due to its advantages regarding a fixed-effect probit estimation (Hsiao, 2003;Badillo & Moreno, 2016) as overcoming the "incidental parameter problem," being appropriate to random samples from large populations or allowing for the treatment of omitted factors.…”

Section: Methodsmentioning

confidence: 99%

Is the corporate social responsibility–innovation link homogeneous?: Looking for sustainable innovation in the Spanish context

García‐Piqueres

García‐Ramos

2019

Corp Soc Responsibility Env

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This study examines if the relationship between corporate social responsibility (CSR) and innovation is homogeneous or depends on the type of CSR practice and/or the type of innovation. The paper focuses on the three dimensions of the “three bottom line” of CSR (economic, social, and environmental) and on the so‐called “fateful triangle” of innovation, which together with studied product and process innovation types also considers organizational innovation. The theoretical framework is based on the resource‐based view and the knowledge‐based view approaches. In analysing sustainable innovation in the Spanish context, we look at a set of firms taking data for the 2009–2014 Spanish Community Innovation Survey. The empirical study uses random effect probit panel data methodology. The results show that, although the positive effect of CSR on innovation is confirmed for the majority of the cases, there are differences depending on the innovation type and the CSR dimension.

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Section: Methodsmentioning

confidence: 99%

Is the corporate social responsibility–innovation link homogeneous?: Looking for sustainable innovation in the Spanish context

García‐Piqueres

García‐Ramos

2019

Corp Soc Responsibility Env

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“…According to Hsiao (2003) and Klevmarken (1989), panel data allows to: (i) control the heterogeneity and differences between regions; (ii) process the information with much more variability, less multicollinearity between the explanatory variables, more degrees of freedom and efficiency; (iii) study the dynamic adjustment of the variables over time; (iv) build and test more sophisticated behavioral models than the sectional or pure temporal; and (v) reduce or eliminate the bias resulting from data aggregation.…”

Section: Methodological Frameworkmentioning

confidence: 99%

Determinants of Regional Growth in Portugal: An Empirical Analysis

Manso¹,

Matos²,

Carvalho³

2015

E&S

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ABSTRACT. This paper aims to define the determinants of regional growth in Portugal, at the NUTS III level, in a time span between 1999 and 2010. A panel data approach is used as well as the fixed, random and pooled effects models, all of them with and without trend. The results from the panel data and the Hausman test show that the model that best portrays the reality under study is the panel data with random effects model. The performed analysis allowed us to confirm that employment, sectorial GVA, electricity consumption, number of museums and landline phone accesses have a positive association with the regional per capita GDP. Surprisingly, the number of residents, population density, number of medical doctors and technical progress presents a negative correlation instead.

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“…Nesse caso, a análi-se de dados em painel assegura, conforme Baltagi (2005), não só um maior controle, mas também a devida consistência dos parâmetros. Ademais, a regressão em painel demonstra com mais propriedade a dinâmica de ajustamento, mudanças e tendências no tempo, proporcionando resultados robustos (KLEVMARKEN, 1989). Em sínte-se, a regressão em painel oferece confiabilidade, sendo capaz de agregar um número maior de informações, o que não seria possível com a utilização, apenas, de séries temporais ou de cortes transversais puros (GUJARATI; PORTER, 2011).…”

Section: Especificações Do Modelo Analíticounclassified

Indutores de impactos ambientais: uma análise comparativa entre BRICS e G7 (1992-2013)

Alvarenga

Sobrinho

2018

REE

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Resumo:O objetivo deste artigo é analisar o impacto ambiental em economias que vivenciam diferentes estágios de desenvolvimento e verificar o comportamento dos indutores população e renda. Para tanto, utiliza-se Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) aplicada ao G7 e aos BRICS. Os resultados mostram que, no período de 1992 a 2013, a população exerceu impacto estatisticamente significativo e positivo para os dois blocos, enquanto a afluência exerceu impacto negativo no G7 e positivo nos BRICS, sendo estatisticamente significativa para ambos. Conclui-se que os esforços dos BRICS para atingir o desenvolvimento se dão à custa de danos ambientais, e que tanto a população quanto a renda explicam o impacto ambiental nesse grupo. Em contraste, países desenvolvidos tendem a diminuir seu impacto à medida que a renda aumenta. Palavras-chave: Impactos Ambientais; STIRPAT; Dados em Painel; BRICS; G7. Inductors of environmental impacts: a comparative analysis between the brics and G7 (1992-2013) Abstract:The objective of this paper is to analyze the environmental impact in economies that have experienced different levels of development, and verify the inducing behavior of population and income. To this end, the Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) applied to BRICS and G7 countries. The results showed that, between 1992 and 2013, population has a statistically significant and positive impact within both blocs, whereas affluence, equally significant, exerts a negative impact within the G7 and a positive one within the BRICS. It can be concluded that the BRICS's efforts to achieve the development take place at the cost of environmental damage, and that both population and income explain the environmental impact within this group. In contrast, developed countries tend to reduce their impact as their income rises.

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Introduction

Cited by 87 publications

References 7 publications

Is the corporate social responsibility–innovation link homogeneous?: Looking for sustainable innovation in the Spanish context

Is the corporate social responsibility–innovation link homogeneous?: Looking for sustainable innovation in the Spanish context

Determinants of Regional Growth in Portugal: An Empirical Analysis

Indutores de impactos ambientais: uma análise comparativa entre BRICS e G7 (1992-2013)

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