7 resultados para Bronzes, Chinese.

em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom


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This paper has three contributions. First, it shows how field work within small firms in PR Chinese has provided new evidence which enables us to measure and calibrate Entrepreneurial Orientation (EO), as ‘spirit’, and Intangible Assets (IA), as ‘material’, for use in models of small firm growth. Second, it uses inter-item correlation analysis and both exploratory and confirmatory factor analysis to provide new measures of EO and IA, in index and in vector form, for use in econometric models of firm growth. Third, it estimates two new econometric models of small firm employment growth in PR China, under the null hypothesis of Gibrat’s Law, using our two new index-based and vector-based measures of EO and IA. Estimation is by OLS with adjustment for heteroscedasticity, and for sample selectivity. Broadly, it finds that EO attributes have had little significant impact on small firm growth, and indeed innovativeness and pro-activity paradoxically may even dampen growth. However, IA attributes have had a positive and significant impact on growth, with networking, and technological knowledge being of prime importance, and intellectual property and human capital being of lesser but still significant importance. In the light of these results, Gibrat’s Law is generalized, and Jovanovic’s learning theory is extended, to emphasise the importance of IA to growth. These findings cast new empirical light on the oft-quoted national slogan in PR China of “spirit and material”. So far as small firms are concerned, this paper suggests that their contribution to PR China’s remarkable economic growth is not so much attributable to the ‘spirit’ of enterprise (as suggested by propaganda) as, more prosaically, to the pursuit of the ‘material’.

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This paper reports on one of the first empirical attempts to investigate small firm growth and survival, and their determinants, in the Peoples’ Republic of China. The work is based on field work evidence gathered from a sample of 83 Chinese private firms (mainly SMEs) collected initially by face-to-face interviews, and subsequently by follow-up telephone interviews a year later. We extend the models of Gibrat (1931) and Jovanovic (1982), which traditionally focus on size and age alone (e.g. Brock and Evans, 1986), to a ‘comprehensive’ growth model with two types of additional explanatory variables: firm-specific (e.g. business planning); and environmental (e.g. choice of location). We estimate two econometric models: a ‘basic’ age-size-growth model; and a ‘comprehensive’ growth model, using Heckman’s two-step regression procedure. Estimation is by log-linear regression on cross-section data, with corrections for sample selection bias and heteroskedasticity. Our results refute a pure Gibrat model (but support a more general variant) and support the learning model, as regards the consequences of size and age for growth; and our extension to a comprehensive model highlights the importance of location choice and customer orientation for the growth of Chinese private firms. In the latter model, growth is explained by variables like planning, R&D orientation, market competition, elasticity of demand etc. as well as by control variables. Our work on small firm growth achieves two things. First, it upholds the validity of ‘basic’ size-age-growth models, and successfully applies them to the Chinese economy. Second, it extends the compass of such models to a ‘comprehensive’ growth model incorporating firm-specific and environmental variables.

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We study the impact of both microeconomic factors and the macroeconomy on the financial distress of Chinese listed companies over a period of massive economic transition, 1995 to 2006. Based on an economic model of financial distress under the institutional setting of state protection against exit, and using our own firm-level measure of distress, we find important impacts of firm characteristics, macroeconomic instability and institutional factors on the hazard rate of financial distress. The results are robust to unobserved heterogeneity at the firm level, as well as those shared by firms in similar macroeconomic founding conditions. Comparison with related studies for other economies highlights important policy implications.

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This paper addresses the hotly-debated question: do Chinese firms overinvest? A firm-level dataset of 100,000 firms over the period of 2000-07 is employed for this purpose. We initially calculate measures of investment efficiency, which is typically negatively associated with overinvestment. Despite wide disparities across various ownership groups, industries and regions, we find that corporate investment in China has become increasingly efficient over time. However, based on direct measures of overinvestment that we subsequently calculate, we find evidence of overinvestment for all types of firms, even in the most efficient and most profitable private sector. We find that the free cash flow hypothesis provides a good explanation for China‟s overinvestment, especially for the private sector, while in the state sector, overinvestment is attributable to the poor screening and monitoring of enterprises by banks.

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This paper is inspired by articles in the last decade or so that have argued for more attention to theory, and to empirical analysis, within the well-known, and long-lasting, contingency framework for explaining the organisational form of the firm. Its contribution is to extend contingency analysis in three ways: (a) by empirically testing it, using explicit econometric modelling (rather than case study evidence) involving estimation by ordered probit analysis; (b) by extending its scope from large firms to SMEs; (c) by extending its applications from Western economic contexts, to an emerging economy context, using field work evidence from China. It calibrates organizational form in a new way, as an ordinal dependent variable, and also utilises new measures of familiar contingency factors from the literature (i.e. Environment, Strategy, Size and Technology) as the independent variables. An ordered probit model of contingency was constructed, and estimated by maximum likelihood, using a cross section of 83 private Chinese firms. The probit was found to be a good fit to the data, and displayed significant coefficients with plausible interpretations for key variables under all the four categories of contingency analysis, namely Environment, Strategy, Size and Technology. Thus we have generalised the contingency model, in terms of specification, interpretation and applications area.

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This paper reports on one of the first empirical attempts to investigate small firm growth and survival, and their determinants, in the Peoples’ Republic of China. The work is based on field work evidence gathered from a sample of 83 Chinese private firms (mainly SMEs) collected initially by face-to-face interviews, and subsequently by follow-up telephone interviews a year later. We extend the models of Gibrat (1931) and Jovanovic (1982), which traditionally focus on size and age alone (e.g. Brock and Evans, 1986), to a ‘comprehensive’ growth model with two types of additional explanatory variables: firm-specific (e.g. business planning); and environmental (e.g. choice of location). We estimate two econometric models: a ‘basic’ age-size-growth model; and a ‘comprehensive’ growth model, using Heckman’s two-step regression procedure. Estimation is by log-linear regression on cross-section data, with corrections for sample selection bias and heteroskedasticity. Our results refute a pure Gibrat model (but support a more general variant) and support the learning model, as regards the consequences of size and age for growth; and our extension to a comprehensive model highlights the importance of location choice and customer orientation for the growth of Chinese private firms. In the latter model, growth is explained by variables like planning, R&D orientation, market competition, elasticity of demand etc. as well as by control variables. Our work on small firm growth achieves two things. First, it upholds the validity of ‘basic’ size-age-growth models, and successfully applies them to the Chinese economy. Second, it extends the compass of such models to a ‘comprehensive’ growth model incorporating firm-specific and environmental variables.

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Adverse selection may thwart trade between an informed seller, who knows the probability p that an item of antiquity is genuine, and an uninformed buyer, who does not know p. The buyer might not be wholly uninformed, however. Suppose he can perform a simple inspection, a test of his own: the probability that an item passes the test is g if the item is genuine, but only f < g if it is fake. Given that the buyer is no expert, his test may have little power: f may be close to g. Unfortunately, without much power, the buyer's test will not resolve the difficulty of adverse selection; gains from trade may remain unexploited. But now consider a "store", where the seller groups a number of items, perhaps all with the same quality, the same probability p of being genuine. (We show that in equilibrium the seller will choose to group items in this manner.) Now the buyer can conduct his test across a large sample, perhaps all, of a group of items in the seller's store. He can thereby assess the overall quality of these items; he can invert the aggregate of his test results to uncover the underlying p; he can form a "prior". There is thus no longer asymmetric information between seller and buyer: gains from trade can be exploited. This is our theory of retailing: by grouping items together - setting up a store - a seller is able to supply buyers with priors, as well as the items themselves. We show that the weaker the power of the buyer�s test (the closer f is to g), the greater the seller�s profit. So the seller has no incentive to assist the buyer � e.g., by performing her own tests on the items, or by cleaning them to reveal more about their true age. The paper ends with an analysis of which sellers should specialise in which qualities. We show that quality will be low in busy locations and high in expensive locations.