Model identification, migration, and investment-specific shocks: Three essays

Abstract

This thesis consists of an introduction and three substantive chapters. Chapter 2 explores the identification of a small open economy model. Chapter 3 focuses on the business cycle consequences of migration. And chapter 4 investigates the contribution of investment-specific technology shocks to business cycle fluctuations in the presence of financial frictions.

Chapter 2 takes a conventional new open economy macro model for a small open economy and addresses three questions: what data series should be used to identify the parameters of such a model? Are foreign data important for the identification of domestic parameters? And lastly, which structural parameters are interdependent?

The chapter illustrates an applied methodology that enables an investigator to understand which data series are informative about parameters. The methodology can also be used to learn about the properties of the model. In particular, the methodology highlights which parameters are connected to which data series. Identification of business cycle models matters because our ability to recover structural parameters is influenced by the data series that are used to inform the estimation. Structural parameters determine both the specification of household preferences and the constraints that affect business cycle volatility, which together determine welfare. Consequently, identification analysis can provide insights into household welfare, which in turn has ramifications for the specification of monetary policy rules.

If parameters are identified then the likelihood will eventually outweigh any prior beliefs as the sample size becomes large (Gelman et al., 2004, p. 107). The approach discussed here thus shows whether data will eventually dominate prior beliefs about parameters, determining whether analysis can – in the limit – resolve conflicting prior beliefs, and therefore usefully inform the design of policy rules.

Chapter 3 of this thesis examines the business cycle effects that arise from an expansion of the population due to migration. In recent years, migration flows have become a highly politicised topic, both in New Zealand and abroad. While the debate on migration has become heated, comparatively little is known about the business cycle consequences of migration flows.

This chapter contributes to the macroeconomic literature by illustrating the contribution that migration shocks make to cyclical fluctuations in New Zealand, and illustrates their dynamic impact. Using an estimated dynamic stochastic general equilibrium (DSGE) model of a small open economy and a structural vector autoregression, the chapter shows that migration shocks account for a considerable portion of the variability of per capita gross domestic product (GDP). While migration shocks matter for the capital investment and consumption components of per capita GDP, other shocks are more important drivers of cyclical fluctuations in these aggregates. Migration shocks also make some contribution to residential investment and real house prices, but other shocks play a more substantial role in driving housing market volatility.

In the DSGE model, the level of human capital possessed by migrants relative to that of locals materially affects the business cycle impact of migration. The impact of migration shocks is larger when migrants have substantially different – larger or smaller – levels of human capital relative to locals. When the average migrant has higher levels of human capital than locals, as seems to be common for migrants into most OECD¹ economies, a migration shock has an expansionary effect on per capita GDP and its components, which also accords with the evidence from a structural vector autoregression.

Chapter 4 of this thesis investigates the contribution of investment-specific technology (IST) shocks in driving cyclical fluctuations in a closed economy model when a borrowing constraint is introduced à la Kiyotaki and Moore (1997). IST shocks have been identified as a major driver of the business cycle, eg see Greenwood et al. (2000), and Justiniano et al. (2010, 2011). These shocks affect the rate at which investment goods are transformed into capital stock, and have been linked to frictions in financial markets, because financial intermediation is instrumental in facilitating investment. The third chapter shows that the importance of these investment shocks is in fact substantially diminished when collateral constraints on firms are introduced into an estimated dynamic stochastic general equilibrium model. In the presence of binding collateral constraints, risk premium shocks, which perturb interest rates and affect intertemporal substitution, supplant IST shocks as important drivers of the business cycle.

¹ Organisation for Economic Cooperation and Development.