The Difference, System and ‘Double-D’ GMM Panel Estimators in the Presence of Structural Breaks

The effects of structural breaks in dynamic panels are more complicated than in time series models as the bias can be either negative or positive. This paper focuses on the effects of mean shifts in otherwise stationary processes within an instrumental variable panel estimation framework. We show the sources of the bias and a Monte Carlo analysis calibrated on United States bank lending data demonstrates the size of the bias for a range of auto-regressive parameters. We also propose additional moment conditions that can be used to reduce the biases caused by shifts in the mean of the data.

Threshold Effects of Dismissal Protection Regulation and the Emergence of Temporary Work Agencies

Labour market regulations aimed at enhancing job-security are dominant in several OECD countries. These regulations seek to reduce dismissals of workers and fluctuations in employment. The main theoretical contribution is to gauge the effects of such regulations on labour demand across establishment sizes. In order to achieve this, we investigate an optimising model of labour demand under uncertainty through the application of real option theory. We also consider other forms of employment which increase the flexibility of the labour market. In particular, we are modelling the contribution of temporary employment agencies (Zeitarbeit) allowing for quick personnel adjustments in client firms. The calibration results indicate that labour market rigidities may be crucial for understanding sluggishness in firms´ labour demand and the emergence and growth of temporary work.

Valuing American Derivatives by Least Squares Methods

Least Squares estimators are notoriously known to generate sub-optimal exercise decisions when determining the optimal stopping time. The consequence is that the price of the option is underestimated. We show how variance reduction methods can be implemented to obtain more accurate option prices. We also extend the Longsta¤ and Schwartz (2001) method to price American options under stochastic volatility. These are two important contributions that are particularly relevant for practitioners. Finally, we extend the Glasserman and Yu (2004b) methodology to price Asian options and basket options.

Optimal Martingales and American Option Pricing

Pricing American options is an interesting research topic since there is no analytical solution to value these derivatives. Different numerical methods have been proposed in the literature with some, if not all, either limited to a specific payoff or not applicable to multidimensional cases. Applications of Monte Carlo methods to price American options is a relatively new area that started with Longstaff and Schwartz (2001). Since then, few variations of that methodology have been proposed. The general conclusion is that Monte Carlo estimators tend to underestimate the true option price. The present paper follows Glasserman and Yu (2004b) and proposes a novel Monte Carlo approach, based on designing "optimal martingales" to determine stopping times. We show that our martingale approach can also be used to compute the dual as described in Rogers (2002).

The Taylor Principle and (In-) Determinacy in a New Keynesian Model with hiring Frictions and Skill Loss

We introduce duration dependent skill decay among the unemployed into a New-Keynesian model with hiring frictions developed by Blanchard/Gali (2008). If the central bank responds only to (current, lagged or expected future) inflation and quarterly skill decay is above a threshold level, determinacy requires a coefficient on inflation smaller than one. The threshold level is plausible with little steady-state hiring and firing ("Continental European Calibration") but implausibly high in the opposite case ("American calibration"). Neither interest rate smoothing nor responding to the output gap helps to restore determinacy if skill decay exceeds the threshold level. However, a modest response to unemployment guarantees determinacy. Moreover, under indeterminacy, both an adverse sunspot shock and an adverse technology shock increase unemployment extremely persistently.

On Identification of Bayesian DSGE Models

In recent years there has been increasing concern about the identification of parameters in dynamic stochastic general equilibrium (DSGE) models. Given the structure of DSGE models it may be difficult to determine whether a parameter is identified. For the researcher using Bayesian methods, a lack of identification may not be evident since the posterior of a parameter of interest may differ from its prior even if the parameter is unidentified. We show that this can even be the case even if the priors assumed on the structural parameters are independent. We suggest two Bayesian identification indicators that do not suffer from this difficulty and are relatively easy to compute. The first applies to DSGE models where the parameters can be partitioned into those that are known to be identified and the rest where it is not known whether they are identified. In such cases the marginal posterior of an unidentified parameter will equal the posterior expectation of the prior for that parameter conditional on the identified parameters. The second indicator is more generally applicable and considers the rate at which the posterior precision gets updated as the sample size (T) is increased. For identified parameters the posterior precision rises with T, whilst for an unidentified parameter its posterior precision may be updated but its rate of update will be slower than T. This result assumes that the identified parameters are pT-consistent, but similar differential rates of updates for identified and unidentified parameters can be established in the case of super consistent estimators. These results are illustrated by means of simple DSGE models.

Spatial Interactions in Hedonic Pricing Models: The Urban Housing Market of Aveiro, Portugal

Spatial heterogeneity, spatial dependence and spatial scale constitute key features of spatial analysis of housing markets. However, the common practice of modelling spatial dependence as being generated by spatial interactions through a known spatial weights matrix is often not satisfactory. While existing estimators of spatial weights matrices are based on repeat sales or panel data, this paper takes this approach to a cross-section setting. Specifically, based on an a priori definition of housing submarkets and the assumption of a multifactor model, we develop maximum likelihood methodology to estimate hedonic models that facilitate understanding of both spatial heterogeneity and spatial interactions. The methodology, based on statistical orthogonal factor analysis, is applied to the urban housing market of Aveiro, Portugal at two different spatial scales.

The distributional consequences of tax reforms under market distortions

In this paper we examine the importance of imperfect competition in product and labour markets in determining the long-run welfare e¤ects of tax reforms assuming agent heterogeneneity in capital hold- ings. Each of these market failures, independently, results in welfare losses for at least a segment of the population, after a capital tax cut and a concurrent labour tax increase. However, when combined in a realistic calibration to the UK economy, they imply that a capital tax cut will be Pareto improving in the long run. Consistent with the the- ory of second-best, the two distortions in this context work to correct the negative distributional e¤ects of a capital tax cut that each one, on its own, creates.

Poor and Sick: Estimating the relationship between Household Income and Health

This study evaluates the effect of the individual‘s household income on their health at the later stages of working life. A structural equation model is utilised in order to derive a composite and continuous index of the latent health status from qualitative health status indicators. The endogenous relationship between health status and household income status is taken into account by using IV estimators. The findings reveal a significant effect of individual household income on health before and after endogeneity is taken into account and after a host of other factors which is known to influence health, including hereditary factors and the individual‘s locus of control. Importantly, it is also shown that the childhood socioeconomic position of the individual has long lasting effects on health as it appears to play a significant role in determining health during the later stages of working life.

Aggregate and welfare effects of long run inflation risk under inflation and price-level targeting

This paper presents a DSGE model in which long run inflation risk matters for social welfare. Aggregate and welfare effects of long run inflation risk are assessed under two monetary regimes: inflation targeting (IT) and price-level targeting (PT). These effects differ because IT implies base-level drift in the price level, while PT makes the price level stationary around a target price path. Under IT, the welfare cost of long run inflation risk is equal to 0.35 percent of aggregate consumption. Under PT, where long run inflation risk is largely eliminated, it is lowered to only 0.01 per cent. There are welfare gains from PT because it raises average consumption for the young and lowers consumption risk substantially for the old. These results are strongly robust to changes in the PT target horizon and fairly robust to imperfect credibility, fiscal policy, and model calibration. While the distributional effects of an unexpected transition to PT are sizeable, they are short-lived and not welfare-reducing.

Indexed versus nominal government debt under inflation and price-level targeting

This paper presents a DSGE model in which long run inflation risk matters for social welfare. Optimal indexation of long-term government debt is studied under two monetary policy regimes: inflation targeting (IT) and price-level targeting (PT). Under IT, full indexation is optimal because long run inflation risk is substantial due to base-level drift, making indexed bonds a much better store of value than nominal bonds. Under PT, where long run inflation risk is largely eliminated, optimal indexation is substantially lower because nominal bonds become a better store of value relative to indexed bonds. These results are robust to the PT target horizon, imperfect credibility of PT and model calibration, but the assumption that indexation is lagged is crucial. From a policy perspective, a key finding is that accounting for optimal indexation has important welfare implications for comparisons of IT and PT.

Complexity and Bounded Rationality in Individual Decision Problemsing.

I develop a model of endogenous bounded rationality due to search costs, arising implicitly from the problems complexity. The decision maker is not required to know the entire structure of the problem when making choices but can think ahead, through costly search, to reveal more of it. However, the costs of search are not assumed exogenously; they are inferred from revealed preferences through her choices. Thus, bounded rationality and its extent emerge endogenously: as problems become simpler or as the benefits of deeper search become larger relative to its costs, the choices more closely resemble those of a rational agent. For a fixed decision problem, the costs of search will vary across agents. For a given decision maker, they will vary across problems. The model explains, therefore, why the disparity, between observed choices and those prescribed under rationality, varies across agents and problems. It also suggests, under reasonable assumptions, an identifying prediction: a relation between the benefits of deeper search and the depth of the search. As long as calibration of the search costs is possible, this can be tested on any agent-problem pair. My approach provides a common framework for depicting the underlying limitations that force departures from rationality in different and unrelated decision-making situations. Specifically, I show that it is consistent with violations of timing independence in temporal framing problems, dynamic inconsistency and diversification bias in sequential versus simultaneous choice problems, and with plausible but contrasting risk attitudes across small- and large-stakes gambles.