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Dynamic activity analysis model-based win-win development forecasting under environment regulations in China

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An Erratum to this article was published on 26 June 2015

Abstract

Porter hypothesis states that environmental regulation may lead to win-win opportunities, that is, improve the productivity and reduce the undesirable output simultaneously. Based on directional distance function, this paper proposes a novel dynamic activity analysis model to forecast the possibilities of win-win development in Chinese industry between 2011 and 2050. The consistent bootstrap estimation procedures are also developed for statistical inference of the point forecasts. The evidence reveals that the appropriate energy-saving and emission-abating regulation will significantly result in both the net growth of potential output and the increasing growth of total factor productivity for most industrial sectors in a statistical sense. This favors Porter hypothesis.

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Notes

  1. Many empirical researches support Porter hypothesis, such as Karvonen (2001); Mohr (2002); Murty and Kumar (2003); Beaumont and Tinch (2004); Cerin (2006); Greaker (2006); Kuosmanen et al. (2009); Groom et al. (2010); Zhang and Choi (2013) There are also a few papers whose conclusion is neutral or against Porter hypothesis, see Boyd and McClelland (1999); Xepapadeas and Zeeuw (1999); Feichtinger et al. (2005).

  2. In this case, the value of \(\beta \) is greater than zero which tell us the sizes of inefficiencies for the unit.

  3. The random sample is generated according to

    $$\begin{aligned} \beta _{w,b}^{i*} = \left\{ \begin{array}{ll} \beta _{w,b}^{i,0*} +h\varepsilon _b^{i*} &{} \quad if\;\beta _{w,b}^{i,0*} +h\varepsilon _b^{i*} \le 1 \\ 2-\beta _{w,b}^{i,0*} -h\varepsilon _b^{i*} &{} \quad \quad otherwise \end{array}\right. \end{aligned}$$

    where \(\left\{ {\beta _{w,b}^{i,0*} ,i=1,2,\ldots ,n} \right\} \) is a simple bootstrap sample from \(\left\{ {\beta _w^i ,i=1,2,\ldots ,n} \right\} \), that is, obtained by drawing with replacement from\(\left\{ {\beta _w^i ,i=1,2,\ldots ,n} \right\} \!,\,\varepsilon _b^{i*}\) is a random drawn from a standard normal, and h is the smoothing parameter of bandwidth.

  4. As Daraio and Simar (2007) denoted, B should be greater than 2,000. The choice of kernel bandwidth controls the smoothness of the probability density curve. Following Simar and Wilson (1998), we choose h \(=\) 0.02 in this paper which provides a reasonably smooth estimate of the distribution function of efficiency scores.

  5. Silverman (1978, 1986) and Härdle (1990) discuss considerations relevant to the choice of h. In the paper, we use Silverman (1986) suggestion for h setting since we are using a bivariate normal kernel.

  6. They are wood processing, general machinery manufacturing, special machinery manufacturing, transport equipment manufacturing, manufacturing of measuring instruments and machinery, and others.

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Acknowledgments

The work is sponsored by Deutsche Forschungsgemeinschaft through SFB 649 “Economic Risk”. The supports from National Natural Science Foundation (71173048), National Social Science Foundation (12AZD047), Ministry of Education (11JJD790007), Shanghai Leading Talent Project and Fudan Zhuo-Shi Talent Plan are also acknowledged.

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Authors and Affiliations

  1. China Center for Economic Studies, School of Economics, Fudan University, Handan Road 220, Shanghai,  200433, China

    Shiyi Chen

  2. Center for Applied Statistics and Economics, Humboldt-Universität zu Berlin, Spandauer Straße 1, 10178 , Berlin, Germany

    Wolfgang K. Härdle

  3. Lee Kong Chian School of Business, Singapore Management University, Singapore, Singapore

    Wolfgang K. Härdle

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  1. Shiyi Chen
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  2. Wolfgang K. Härdle
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Correspondence to Shiyi Chen.

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Chen, S., Härdle, W.K. Dynamic activity analysis model-based win-win development forecasting under environment regulations in China. Comput Stat 29, 1543–1570 (2014). https://doi.org/10.1007/s00180-014-0505-2

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