Understanding Liquidity and Credit Risks in the Financial Crisis

This paper develops a structured dynamic factor model for the spreads between London Interbank Offered Rate (LIBOR) and overnight index swap (OIS) rates for a panel of banks. Our model involves latent factors which reflect liquidity and credit risk. Our empirical results show that surges in the short term LIBOR-OIS spreads during the 2007-2009 fi nancial crisis were largely driven by liquidity risk. However, credit risk played a more signifi cant role in the longer term (twelve-month) LIBOR-OIS spread. The liquidity risk factors are more volatile than the credit risk factor. Most of the familiar events in the financial crisis are linked more to movements in liquidity risk than credit risk.

Pension reform in a rapidly ageing country: the case of Ukraine

Ukraine has a rapidly ageing and declining population. A dynamic forward-­looking Computable General Equilibrium (CGE) model with an explicitly modelled Pay‐As‐You-­Go pension scheme is constructed to perform simulations of different pension reform scenarios and investigate the impact of population ageing on a wide range of macroeconomic variables. It is shown that, changes in age structure will result in a significant negative impact on the economy and stability of the pension system. Analysis of the potential changes to the pension system is limited to modelling an increase of the pension age, keeping either the workers’ contribution rate or replacement rate constant.

UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?

Block factor methods offer an attractive approach to forecasting with many predictors. These extract the information in these predictors into factors reflecting different blocks of variables (e.g. a price block, a housing block, a financial block, etc.). However, a forecasting model which simply includes all blocks as predictors risks being over-parameterized. Thus, it is desirable to use a methodology which allows for different parsimonious forecasting models to hold at different points in time. In this paper, we use dynamic model averaging and dynamic model selection to achieve this goal. These methods automatically alter the weights attached to different forecasting model as evidence comes in about which has forecast well in the recent past. In an empirical study involving forecasting output and inflation using 139 UK monthly time series variables, we find that the set of predictors changes substantially over time. Furthermore, our results show that dynamic model averaging and model selection can greatly improve forecast performance relative to traditional forecasting methods.

Optimal taxation and the skill premium

The stylized facts suggest a negative relationship between tax progressivity and the skill premium from the early 1960s until the early 1990s, and a positive one thereafter. They also generally imply rising tax progressivity, except for the 1980s. In this paper, we ask whether optimal tax policy is consistent with these observations, taking into account the demographic and technological factors that have also affected the skill premium. To this end, we construct a dynamic general equilibrium model in which the skill premium and the progressivity of the tax system are endogenously determined, with the latter being optimally chosen by a benevolent government. We find that optimal policy delivers both a progressive tax system and model predictions which are generally consistent, except for the 1980s, with the stylized facts relating to the skill premium and progressivity. To capture the patterns in the data over the 1980s requires that we adopt a government policy which is biased towards the interests of skilled agents. Thus, in addition to demographic and technological factors, changes in the preferences of policy-makers appear to be a potentially important factor in determining the evolution of the observed skill premium.

Large Time-Varying Parameter VARs

In this paper we develop methods for estimation and forecasting in large timevarying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the TVP-VAR so that its dimension can change over time. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our approach.

Finite Horizon Learning

Incorporating adaptive learning into macroeconomics requires assumptions about how agents incorporate their forecasts into their decision-making. We develop a theory of bounded rationality that we call finite-horizon learning. This approach generalizes the two existing benchmarks in the literature: Eulerequation learning, which assumes that consumption decisions are made to satisfy the one-step-ahead perceived Euler equation; and infinite-horizon learning, in which consumption today is determined optimally from an infinite-horizon optimization problem with given beliefs. In our approach, agents hold a finite forecasting/planning horizon. We find for the Ramsey model that the unique rational expectations equilibrium is E-stable at all horizons. However, transitional dynamics can differ significantly depending upon the horizon.

Stability of Growth Models with Generalised Lag Structures

This paper considers the lag structures of dynamic models in economics, arguing that the standard approach is too simple to capture the complexity of actual lag structures arising, for example, from production and investment decisions. It is argued that recent (1990s) developments in the the theory of functional differential equations provide a means to analyse models with generalised lag structures. The stability and asymptotic stability of two growth models with generalised lag structures are analysed. The paper concludes with some speculative discussion of time-varying parameters.

Forward Looking and Myopic Regional Computable General Equilibrium Models. How Significant is the Distinction?

We present a stylized intertemporal forward-looking model able that accommodates key regional economic features, an area where the literature is not well developed. The main difference, from the standard applications, is the role of saving and its implication for the balance of payments. Though maintaining dynamic forward-looking behaviour for agents, the rate of private saving is exogenously determined and so no neoclassical financial adjustment is needed. Also, we focus on the similarities and the differences between myopic and forward-looking models, highlighting the divergences among the main adjustment equations and the resulting simulation outcomes.

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.

The Impact of Population Ageing on the Labour Market: Evidence from Overlapping Generations Computable General Equilibrium (OLG-CGE) Model of Scotland

This paper presents a dynamic Overlapping Generations Computable General Equilibrium (OLG-CGE) model of Scotland. The model is used to examine the impact of population ageing on the labour market. More specifically, it is used to evaluate the effects of labour force decline and labour force ageing on key macro-economic variables. The second effect is assumed to operate through age-specific productivity and labour force participation. In the analysis, particular attention is paid to how population ageing impinges on the government expenditure constraint. The basic structure of the model follows in the Auerbach and Kotlikoff tradition. However, the model takes into consideration directly age-specific mortality. This is analogous to “building in” a cohort-component population projection structure to the model, which allows more complex and more realistic demographic scenarios to be considered.

The Growth in Inter-connectedness in the Scottish Economy, 1998-2007; a disaggregated analysis

The measurement of inter-connectedness in an economy using input-output tables is not new, however much of the previous literature has not had any explicit dynamic dimension. Studies have tried to estimate the degree of inter-relatedness for an economy at a given point in time using one input-output table, some have compared different economies at a point in time but few have looked at the question of how interconnectedness within an economy changes over time. The publication in 2010 of a consistent series of input-output tables for Scotland offers the researcher the opportunity to track changes in the degree of inter-connectedness over the seven year period 1998 to 2007. The paper is in two parts. A simple measure of inter-connectedness is introduced in the first part of the paper and applied to the Scottish tables. In the second part of the paper an extraction method is applied to sector by sector to the tables in order to estimate how interconnectedness has changed over time for each industrial sector.

The Impact of Population Ageing on the Labour Market: Evidence from Overlapping Generations Computable General Equilibrium (OLG-CGE) Model of Scotland

This paper presents a dynamic Overlapping Generations Computable General Equilibrium (OLG-CGE) model of Scotland. The model is used to examine the impact of population ageing on the labour market. More specifically, it is used to evaluate the effects of labour force decline and labour force ageing on key macro-economic variables. The second effect is assumed to operate through age-specific productivity and labour force participation. In the analysis, particular attention is paid to how population ageing impinges on the government expenditure constraint. The basic structure of the model follows in the Auerbach and Kotlikoff tradition. However, the model takes into consideration directly age-specific mortality. This is analogous to “building in” a cohort-component population projection structure to the model, which allows more complex and more realistic demographic scenarios to be considered.

Obesity and smoking: can we catch two birds with one tax?

The debate on tobacco and fat taxes often treats smoking and eating as independent behaviors. However, the available evidence shows that they are interdependent, which implies that policies against smoking or obesity may have larger scope than expected. To address this issue, we propose a dynamic rational model where eating and smoking are simultaneous choices that jointly affect body weight and addiction to smoking. Focusing on direct and cross-price effects, we compare tobacco taxes and food taxes and we show that a single policy tool can reduce both smoking and body weight. In particular, food taxes can be more effective than tobacco taxes at simultaneously fighting obesity and smoking.

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.

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.