The Dynamics of UK and US Inflation Expectations

This paper investigates the relationship between short term and long term in ation expectations in the US and the UK with a focus on iflation pass through (i.e. how changes in short term expectations affect long term expectations). An econometric methodology is used which allows us to uncover the relationship between in ation pass through and various explanatory variables. We relate our empirical results to theoretical models of anchored, contained and unmoored inflation expectations. For neither country do we find anchored or unmoored inflation expectations. For the US, contained inflation expectations are found. For the UK, our ndings are not consistent with the specifi =c model of contained inflation expectations presented here, but are consistent with a more broad view of expectations being constrained by the existence of an inflation target.

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.

Estimating Phillips Curves in Turbulent Times using the ECB’s Survey of Professional Forecasters

This paper uses forecasts from the European Central Bank's Survey of Professional Forecasters to investigate the relationship between inflation and inflation expectations in the euro area. We use theoretical structures based on the New Keynesian and Neoclassical Phillips curves to inform our empirical work. Given the relatively short data span of the Survey of Professional Forecasters and the need to control for many explanatory variables, we use dynamic model averaging in order to ensure a parsimonious econometric speci cation. We use both regression-based and VAR-based methods. We find no support for the backward looking behavior embedded in the Neo-classical Phillips curve. Much more support is found for the forward looking behavior of the New Keynesian Phillips curve, but most of this support is found after the beginning of the financial crisis.

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.

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

Official Central Bank Interventions in the Foreign Exchange Markets: A DCC Approach with Exogenous Variables

This paper assesses the impact of official central bank interventions (CBIs) on exchange rate returns, their volatility and bilateral correlations. By exploiting the recent publication of intervention data by the Bank of England, this study is able to investigate fficial interventions by a total number of four central banks, while the previous studies have been limited to three (the Federal Reserve, Bundesbank and Bank of Japan). The results of the existing literature are reappraised and refined. In particular, unilateral CBI is found to be more successful than coordinated CBI. The likely implications of these findings are then discussed.

The Role of Institutions in Cross-Section Income and Panel Data Growth Models: A Deeper Investigation on the Weakness and Proliferation of Instruments

This paper investigates the role of institutions in determining per capita income levels and growth. It contributes to the empirical literature by using different variables as proxies for institutions and by developing a deeper analysis of the issues arising from the use of weak and too many instruments in per capita income and growth regressions. The cross-section estimation suggests that institutions seem to matter, regardless if they are the only explanatory variable or are combined with geographical and integration variables, although most models suffer from the issue of weak instruments. The results from the growth models provides some interesting results: there is mixed evidence on the role of institutions and such evidence is more likely to be associated with law and order and investment profile; government spending is an important policy variable; collapsing the number of instruments results in fewer significant coefficients for institutions.

Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables

Macroeconomists working with multivariate models typically face uncertainty over which (if any) of their variables have long run steady states which are subject to breaks. Furthermore, the nature of the break process is often unknown. In this paper, we draw on methods from the Bayesian clustering literature to develop an econometric methodology which: i) finds groups of variables which have the same number of breaks; and ii) determines the nature of the break process within each group. We present an application involving a five-variate steady-state VAR.

Using VARs and TVP-VARs with Many Macroeconomic Variables

This paper discusses the challenges faced by the empirical macroeconomist and methods for surmounting them. These challenges arise due to the fact that macroeconometric models potentially include a large number of variables and allow for time variation in parameters. These considerations lead to models which have a large number of parameters to estimate relative to the number of observations. A wide range of approaches are surveyed which aim to overcome the resulting problems. We stress the related themes of prior shrinkage, model averaging and model selection. Subsequently, we consider a particular modelling approach in detail. This involves the use of dynamic model selection methods with large TVP-VARs. A forecasting exercise involving a large US macroeconomic data set illustrates the practicality and empirical success of our approach.

An Empirical Examination of the R&D Boundaries of the Firm - A Problem-Solving Perspective

We consider, both theoretically and empirically, how different organization modes are aligned to govern the efficient solving of technological problems. The data set is a sample from the Chinese consumer electronics industry. Following mainly the problem solving perspective (PSP) within the knowledge based view (KBV), we develop and test several PSP and KBV hypotheses, in conjunction with competing transaction cost economics (TCE) alternatives, in an examination of the determinants of the R&D organization mode. The results show that a firm’s existing knowledge base is the single most important explanatory variable. Problem complexity and decomposability are also found to be important, consistent with the theoretical predictions of the PSP, but it is suggested that these two dimensions need to be treated as separate variables. TCE hypotheses also receive some support, but the estimation results seem more supportive of the PSP and the KBV than the TCE.

The Known Unknowns of Governance.

Empirical researchers interested in how governance shapes various aspects of economic development frequently use the Worldwide Governance indicators (WGI). These variables come in the form of an estimate along with a standard error reflecting the uncertainty of this estimate. Existing empirical work simply uses the estimates as an explanatory variable and discards the information provided by the standard errors. In this paper, we argue that the appropriate practice should be to take into account the uncertainty around the WGI estimates through the use of multiple imputation. We investigate the importance of our proposed approach by revisiting in three applications the results of recently published studies. These applications cover the impact of governance on (i) capital flows; (ii) international trade; (iii) income levels around the world. We generally find that the estimated effects of governance are highly sensitive to the use of multiple imputation. We also show that model misspecification is a concern for the results of our reference studies. We conclude that the effects of governance are hard to establish once we take into account uncertainty around both the WGI estimates and the correct model specification.