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1 – 10 of 139Shaopeng Zhang, Xiaohong Wang and Ben Zhang
The purpose of this paper is to examine the influence of the innovation ability of universities (IAU) on the efficiency of University–Industry knowledge flow and investigate…
Abstract
Purpose
The purpose of this paper is to examine the influence of the innovation ability of universities (IAU) on the efficiency of University–Industry knowledge flow and investigate whether the level of provincial innovative agglomeration (PIA) moderates the relationship between IAU and the efficiency of the University–Industry knowledge flow.
Design/methodology/approach
This study uses the super-efficiency data envelopment analysis model to measure knowledge research efficiency (KRE) and knowledge transformation efficiency (KTE) and then studies the influencing mechanism of the two kinds of efficiency using the spatial Tobit model with panel data from 2008 to 2017.
Findings
The results show that the overall KRE in Chinese universities is higher than the KTE. IAU has a significantly positive impact on KRE and KTE. PIA has a significantly inverted U-shaped influence on KRE and KTE and positively moderates the promoting effect of IAU on KRE and KTE.
Research limitations/implications
Due to the limitations of the data, this paper only selects several secondary indicators to measure KRE and KTE with reference to previous studies.
Practical implications
This study enriches the future research of University–Industry cooperation and knowledge flow and it is conducive to promoting the efficiency of University–Industry knowledge research and transformation from the perspective of universities, enterprises and local governments.
Originality/value
This study proposes the concept of University–Industry knowledge flow and divides the knowledge flow into the knowledge research stage and the knowledge transformation stage based on the knowledge supply chain theory. Moreover, the paper expands the theoretical framework of the impact of IAU on the efficiency of University–Industry knowledge flow and provides findings on the moderating effect of PIA.
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Namhyun Kim, Patrick Wongsa-art and Ian J. Bateman
In this chapter, the authors contribute toward building a better understanding of farmers’ responses to behavioral drivers of land-use decision by establishing an alternative…
Abstract
In this chapter, the authors contribute toward building a better understanding of farmers’ responses to behavioral drivers of land-use decision by establishing an alternative analytical procedure, which can overcome various drawbacks suffered by methods currently used in existing studies. Firstly, our procedure makes use of spatially high-resolution data, so that idiosyncratic effects of physical environment drivers, e.g., soil textures, can be explicitly modeled. Secondly, we address the well-known censored data problem, which often hinders a successful analysis of land-use shares. Thirdly, we incorporate spatial error dependence (SED) and heterogeneity in order to obtain efficiency gain and a more accurate formulation of variances for the parameter estimates. Finally, the authors reduce the computational burden and improve estimation accuracy by introducing an alternative generalized method of moments (GMM)–quasi maximum likelihood (QML) hybrid estimation procedure. The authors apply the newly proposed procedure to spatially high-resolution data in England and found that, by taking these features into consideration, the authors are able to formulate conclusions about causal effects of climatic and physical environment, and environmental policy on land-use shares that differ significantly from those made based on methods that are currently used in the literature. Moreover, the authors show that our method enables derivation of a more effective predictor of the land-use shares, which is utterly useful from the policy-making point of view.
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China's increasing income inequality might cause a series of problems, such as the slowdown of economic growth, social and economic tension, the decline of the ecological…
Abstract
Purpose
China's increasing income inequality might cause a series of problems, such as the slowdown of economic growth, social and economic tension, the decline of the ecological environment quality and the threat to citizens' health. Consequently, income inequality will inevitably affect the ecological well-being performance (EWP) level of China's provinces through the above aspects. Analyzing the impact of income inequality on EWP and its spatial spillover effects are conducive to improving the level of EWP in China. Therefore, the research purpose of this paper is to use China's provincial data from 2001 to 2017 to analyze the impact of income inequality on EWP and the spatial spillover effect based on the evaluation of the EWP value of each province.
Design/methodology/approach
At first, this study utilizes the super efficiency slacks-based measure model (Super-SBM model) to calculate the EWP values of 30 provinces in China, which can evaluate and rank the effective decision units in the SBM model and make up for the defect that the effective decision units cannot be distinguished. Then this study applies the spatial Durbin model and Tobit regression model (SDM-Tobit model) to explore the impact of income inequality and other influencing factors on EWP and the spatial spillover effects in adjacent areas.
Findings
Firstly, the average EWP in China fluctuated slightly and showed a downward trend from 2001 to 2017. In addition, the EWP values of the provinces in the western region are usually weaker than those in the eastern and central regions. Moreover, income inequality is negatively correlated with EWP, and the EWP has a spatial spillover effect, which means the EWP level in a region is affected by EWP values in the adjacent regions. Furthermore, the industrial structure and urbanization level are both negatively related to EWP, while technology level, investment openness, trade openness and education level are positively related to EWP.
Originality/value
Compared with the existing research, the possible contribution of this research is that it takes income inequality as one of the important influencing factors of EWP and adopts the SDM-Tobit model to analyze the impact mechanism of income inequality on EWP from the perspective of time and space, providing new ideas for improving the EWP of various provinces in China.
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Xinzhong Li and Seung-Rok Park
The purpose of this paper is to indicate trade characteristics of Foreign direct investment (FDI) inflows in China and examine the dynamic interaction between FDI inflows and…
Abstract
Purpose
The purpose of this paper is to indicate trade characteristics of Foreign direct investment (FDI) inflows in China and examine the dynamic interaction between FDI inflows and China’s international trade through empirical analysis.
Design/methodology/approach
At first, this paper builds the probability distribution model (Poisson and negative binomial (NB)) to capture the characteristics of spatial distribution of all kinds of FDI firms in Chinese cities and provinces based on count data, so as to indicate the potentials for further introducing FDI inflows in China; Second, this paper investigates the effects of trade on FDI firms inflows based on probability regress model (Binary Logit, Tobit, NB, Poisson, zero inflated negative binomial) and shows how international trade accelerates the different kinds of FDI firms to agglomerate in Eastern, Middle and Western region by the endowments of factors; third, this paper empirically examines the magnitude and characteristics of trade effects generated by FDI inflows by building dynamic panel model based on continuous data.
Findings
First, statistical tests of probability distribution model based on count data show that there are characteristics of spatial agglomeration of FDI firms such as manufacture firm, R & D firm, managing and marketing firm and total sectors, which obey NB distribution as whole; Second, this study indicate that FDI inflows have strong positive effects on the international trade in China’s provinces and on China’s regional trade, and that most of foreign firms in China are export oriented being strongly characterized as labor-intensive industries, especially, contributions of FDI to imports are greater than the contributions of FDI to exports in China’s Middle and Western trade, and the growth of FDI trade in China’s trade volume has been strong over the past years; third, the empirical results of models based on count data and continuous data indicate that FDI inflows have significantly positive relationship with international trade, that is, the relationship between FDI and international trade in the case of China is the characteristics with complement and imports substituting relationship.
Research limitations/implications
Because of mixed data set for FDI inflows of processing and assembling trade and production-oriented FDI, efficiency-seeking and knowledge or technology – intensive FDI inflows in the past 36 years, the paper only investigate characteristics of FDI inflows in China before the turning point of financial crisis, but it is important for capturing the whole picture of trade characteristics of FDI inflows in China.
Practical implications
The derived quantitative results imply that there are still greater potentials for further introducing FDI inflows in China, and decision-maker should make policy of introducing FDI inflows which are favorable to supporting innovative activities and economic agglomeration, and preferably encourage efficiency-seeking and export-oriented FDI inflows so as enhance quality and efficiency of economic growth, which are also helpful to accelerate upgrade of Chinese industry and gradually shorten gap of growth among Eastern, Middle and Western region.
Social implications
FDI inflows in China not only stimulate the remarkable growth of bilateral trade between host country and home country, but also promote the growth of international trade between China and the rest of the world. Thus, policies of bilateral or multilateral free-trade and investment area should be encouraged, which will be also favorable to promote the growth and welfare in all the regions.
Originality/value
This paper demonstrates that spatial distributions of FDI firms in Chinese cities and provinces obey NB probability distribution pattern, and puts forward the methodology of model based on count data and continuous data. Besides, this paper quantitatively indicates trade characteristics of FDI inflows in China as well as the dynamic interaction between FDI inflows and China’s international trade.
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James P. LeSage and R. Kelley Pace
For this discussion, assume there are n sample observations of the dependent variable y at unique locations. In spatial samples, often each observation is uniquely associated with…
Abstract
For this discussion, assume there are n sample observations of the dependent variable y at unique locations. In spatial samples, often each observation is uniquely associated with a particular location or region, so that observations and regions are equivalent. Spatial dependence arises when an observation at one location, say y i is dependent on “neighboring” observations y j, y j∈ϒi. We use ϒi to denote the set of observations that are “neighboring” to observation i, where some metric is used to define the set of observations that are spatially connected to observation i. For general definitions of the sets ϒi,i=1,…,n, typically at least one observation exhibits simultaneous dependence, so that an observation y j, also depends on y i. That is, the set ϒj contains the observation y i, creating simultaneous dependence among observations. This situation constitutes a difference between time series analysis and spatial analysis. In time series, temporal dependence relations could be such that a “one-period-behind relation” exists, ruling out simultaneous dependence among observations. The time series one-observation-behind relation could arise if spatial observations were located along a line and the dependence of each observation were strictly on the observation located to the left. However, this is not in general true of spatial samples, requiring construction of estimation and inference methods that accommodate the more plausible case of simultaneous dependence among observations.
Mizan Rahman and Nafeez Fatima
The purpose of this paper is to look at various dimensions of entrepreneurship and the empirical models that try to explain the relationship between entrepreneurship and growth in…
Abstract
Purpose
The purpose of this paper is to look at various dimensions of entrepreneurship and the empirical models that try to explain the relationship between entrepreneurship and growth in cities for both developed (USA and Europe) and developing countries.
Design/methodology/approach
This paper provides an in‐depth and extensive review of the existing literature on entrepreneurship and economic growth in cities. In most empirical studies, the growth rate of employment or unemployment rate is used as the dependent variable to analyze the effect of entrepreneurship on development. The important independent variables other than entrepreneurship (new start‐ups) are localization, urbanization, level of education, age, industry structure (specialization vs competition), monopoly or competition. The economic units considered for cities are labor market areas (LMAs), standard metropolitan areas (SMAs) and consolidated metropolitan statistical areas (CMSAs). The majority of studies have utilized discrete dependent variable models such as Tobit or Probit to calculate the probability of the effect of entrepreneurship on economic growth. Other studies have applied ordinary least squares estimation to find the cross‐sectional variation of employment growth that accounts for entrepreneurial activities. Panel data are employed in a number of models to control for region‐specific and country‐specific fixed effects.
Findings
In this paper, four important dimensions of entrepreneurship are identified. First, for entrepreneurial studies on economic growth, cities are considered to be appropriate economic units rather than states or countries. Second, there are several definitions and measurements of entrepreneurship available in the literature. Hence, empirical models and their results may vary depending on the model specification. Third, the relationship between employment growth (a proxy for economic growth) and innovative activity is dynamic in nature and thus the problem of endogeneity needs to be addressed. And, finally, entrepreneurship has a spatial dimension and that characteristic must be incorporated into the urban and regional models of entrepreneurship. Three different types of urban models are chosen to reflect these four central dimensions of entrepreneurship. All three urban models confirm the hypothesis that there exists a statistically significant and positive relationship between entrepreneurship and growth in cities. However, the causality of the relationship is not well established.
Originality/value
A critical and in‐depth summary of existing quantitative work on entrepreneurship and economic growth in different cities is the original contribution of the paper.
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Roman Liesenfeld, Jean-François Richard and Jan Vogler
We propose a generic algorithm for numerically accurate likelihood evaluation of a broad class of spatial models characterized by a high-dimensional latent Gaussian process and…
Abstract
We propose a generic algorithm for numerically accurate likelihood evaluation of a broad class of spatial models characterized by a high-dimensional latent Gaussian process and non-Gaussian response variables. The class of models under consideration includes specifications for discrete choices, event counts and limited-dependent variables (truncation, censoring, and sample selection) among others. Our algorithm relies upon a novel implementation of efficient importance sampling (EIS) specifically designed to exploit typical sparsity of high-dimensional spatial precision (or covariance) matrices. It is numerically very accurate and computationally feasible even for very high-dimensional latent processes. Thus, maximum likelihood (ML) estimation of high-dimensional non-Gaussian spatial models, hitherto considered to be computationally prohibitive, becomes feasible. We illustrate our approach with ML estimation of a spatial probit for US presidential voting decisions and spatial count data models (Poisson and Negbin) for firm location choices.
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Rafael Terra and Enlinson Mattos
The purpose of this paper is to investigate the role played by the geographic distance between the poor and non‐poor in the local demand for income redistribution and, in…
Abstract
Purpose
The purpose of this paper is to investigate the role played by the geographic distance between the poor and non‐poor in the local demand for income redistribution and, in particular, to provide an empirical test of the geographically limited altruism model proposed by Pauly, incorporating the possibility of participation costs associated with the provision of transfers.
Design/methodology/approach
First, the authors motivate the discussion by allowing for an “iceberg cost” as participation for the poor individuals in Pauly's original model. Next, using data from the 2000 Brazilian Census and a panel based on the National Household Sample Survey (PNAD) from 2001 to 2007, the authors estimate the effect of the proximity between poor and non‐poor on the demand for redistribution.
Findings
All of the authors' distance‐related explanatory variables indicate that an increased proximity between poor and non‐poor is associated with better targeting of the programs (demand for redistribution). For instance, a one‐hour increase in the time spent commuting by the poor reduces the targeting by 3.158 percentage points. This result is similar to that of Ashworth et al., but is definitely not due to the program leakages. To empirically disentangle participation costs and spatially restricted altruism effects, an additional test is conducted using unique panel data based on the 2004 and 2006 PNAD, which assess the number of benefits and the average benefit value received by beneficiaries. The estimates suggest that both cost and altruism play important roles in the demand for redistribution and might reduce targeting in Brazil. Lastly, the results indicate that “size matters”; i.e. the budget for redistribution has a positive impact on targeting.
Practical implications
Our results suggest that a totally centralized supply of transfers may be more inefficient than local redistribution in terms of targeting, either due to higher participation costs or because of the eventual greater geographical distance between the national median voter and poor individuals. However, a partial role for the federal government, such as providing funds for redistribution, seems to improve targeting.
Originality/value
In particular, the paper provides an empirical test for the geographically limited altruism model proposed by Pauly, incorporating the possibility of participation costs associated with the provision of transfers. The authors motivate this discussion by adding the possibility of distance‐related “iceberg costs” of delivering benefits to poor individuals and show that these two effects of distance may act to lower the demand for transfers, making it difficult to distinguish between the two effects. These two effects of distance act by lowering the demand for transfers, making it difficult to disentangle the effect of altruism from the effect of cost. The authors' empirical strategy seems to allow to identify each of them and to provide a suggestion on whether it is advantageous to carry out redistribution at the local level.
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Yang Yang, Graziano Abrate and Chunrong Ai
This chapter provides an overview of the status of applied econometric research in hospitality and tourism management and outlines the econometric toolsets available for…
Abstract
This chapter provides an overview of the status of applied econometric research in hospitality and tourism management and outlines the econometric toolsets available for quantitative researchers using empirical data from the field. Basic econometric models, cross-sectional models, time-series models, and panel data models are reviewed first, followed by an evaluation of relevant applications. Next, econometric modeling topics that are germane to hospitality and tourism research are discussed, including endogeneity, multi-equation modeling, causal inference modeling, and spatial econometrics. Furthermore, major feasibility issues for applied researchers are examined based on the literature. Lastly, recommendations are offered to promote applied econometric research in hospitality and tourism management.
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Kangyin Dong, Jianda Wang and Xiaohang Ren
The purpose of this study is to examine the spatial fluctuation spillover effect of green total factor productivity (GTFP) under the influence of Internet development.
Abstract
Purpose
The purpose of this study is to examine the spatial fluctuation spillover effect of green total factor productivity (GTFP) under the influence of Internet development.
Design/methodology/approach
Using panel data from 283 cities in China for the period 2003–2016, this paper explores the spatial fluctuation spillover effect of internet development on GTFP by applying the spatial autoregressive with autoregressive conditional heteroscedasticity model (SARspARCH).
Findings
The results of Moran's I test of the residual term and the Bayesian information criterion (BIC) value indicate that the GTFP has a spatial fluctuation spillover effect, and the estimated results of the SARspARCH model are more accurate than the spatial autoregressive (SAR) model and the spatial autoregressive conditional heteroscedasticity (spARCH) model. Specifically, the internet development had a positive spatial fluctuation spillover effect on GTFP in 2003, 2011, 2012 and 2014, and the volatility spillover effect weakens the positive spillover effect of internet development on GTFP. Moreover, Internet development has a significant positive spatial fluctuation spillover effect on GTFP averagely in eastern China and internet-based cities.
Research limitations/implications
The results of this study provide digital solutions for policymakers in improving the level of GTFP in China, with more emphasis on regional synergistic governance to ensure growth.
Originality/value
This paper expands the research ideas for spatial econometric models and provides a more valuable reference for China to achieve green development.
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