Seigniorage-maximizing inflation

What is the seigniorage-maximizing level of inflation? Four models formulae for the seigniorage maximizing inflation rate (SMIR) are compared. Two sticky-price models arrive at very different quantitative recommendations although both predict somewhat lower SMIRs than Cagan’s formula and a variant of a .ex-price model due to Kimbrough (2006). The models differ markedly in how inflation distorts the labour market: The Calvo model implies that inflation and output are negatively related and that output is falling in price stickiness whilst the Rotemberg cost-of-price-adjustment model implies exactly the opposite. Interestingly, if our version of the Calvo model is to be believed, the level of inflation experienced recently in advanced economies such as the USA and the UK may be quite close to the SMIR.

Institutions and the Scale Effect

Growth models which imply a scale effect are commonly refuted on the basis of empirical evidence. A focus on the extent of the market as opposed to the scale of the country has led recent studies to reconsider the role that country scale plays when conditioning on other factors. We consider a variant of a simple learning by doing model to account for the potential role for institutions in determining the strength – and direction – of the scale effect. Using cross-country data, we find a significant interaction between property rights institutions and the effect of scale on long-run growth: In countries with poor property rights institutions, scale is positively related with income per capita; where property rights institutions are good, higher scale is associated with lower per capita ncomes. We find no evidence of such role for contracting institutions.

Growth and Survival Determinants of Chinese Private Firms: Fieldwork evidence and econometric estimates

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.

Growth and Survival Determinants of Chinese Private Firms: Fieldwork evidence and econometric estimates

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.