Entrepreneurial Orientation, Intangible Assets and Firm Growth: the impact of ‘Spirit and Material’ on the growth of Chinese private firms

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’.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.