5 resultados para face age
em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom
Resumo:
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.
Resumo:
Strong hysteresis in the labour market (see Cross, 1995) requires workers to be heterogeneous in terms of the cost of hiring and firing. We show how such heterogeneity arises naturally in labour markets due to differences in workers’ age by showing that both the hiring and the firing thresholds for productivity are age dependent. The presence of strong hysteresis does not for this reason depend on ad-hoc differences in the cost of hiring and firing workers.
Resumo:
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.
Resumo:
In contrast to previous results combining all ages we find positive effects of comparison income on happiness for the under 45s, and negative effects for those over 45. In the BHPS these coefficients are several times the magnitude of own income effects. In GSOEP they cancel to give no effect of effect of comparison income on life satisfaction in the whole sample, when controlling for fixed effects, and time-in-panel, and with flexible, age-group dummies. The residual age-happiness relationship is hump-shaped in all three countries. Results are consistent with a simple life cycle model of relative income under uncertainty.
Resumo:
We first confirm previous results with the German Socio-Economic Panel by Layard et al. (2010), and obtain strong negative effects of comparison income. However, when we split the sample by age, we find quite different results for reference income. The effects on lifesatisfaction are positive and significant for those under 45, consistent with Hirschman’s (1973) ‘tunnel effect’, and only negative (and larger than in the full sample) for those over 45, when relative deprivation dominates. Thus for young respondents, reference income’s signalling role, indicating potential future prospects, can outweigh relative deprivation effects. Own-income effects are also larger for the older sample, and of greater magnitude than the comparison income effect. In East Germany the reference income effects are insignificant for all. With data from the British Household Panel Survey, we confirm standard results when encompassing all ages, but reference income loses significance in both age groups, and most surprisingly, even own income becomes insignificant for those over 45, while education has significant negative effects.