Counterfactual analysis in macroeconometrics: an empirical investigation into the effects of quantitative easing

This paper is concerned with ex ante and ex post counterfactual analyses in the case of macroeconometric applications where a single unit is observed before and after a given policy intervention. It distinguishes between cases where the policy change affects the model’s parameters and where it does not. It is argued that for ex post policy evaluation it is important that outcomes are conditioned on ex post realized variables that are invariant to the policy change but nevertheless influence the outcomes. The effects of the control variables that are determined endogenously with the policy outcomes can be solved out for the policy evaluation exercise. An ex post policy ineffectiveness test statistic is proposed. The analysis is applied to the evaluation of the effects of the quantitative easing (QE) in the UK after March 2009. It is estimated that a 100 basis points reduction in the spread due to QE has an impact effect on output growth of about one percentage point, but the policy impact is very quickly reversed with no statistically significant effects remaining within 9-12 months of the policy intervention

Estimation and Inference in Short Panel Vector Autoregressions with Unit Roots and Cointegration

This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and shown to be consistent and asymptotically normally distributed irrespective of the unit root and cointegrating properties of the underlying PVAR model. The transformed likelihood framework is also used to derive unit root and cointegration tests in panels with short time dimension; these tests have the attractive feature that they are based on standard chi-squared and normal distributed statistics. Examining Generalised Method of Moments (GMM) estimation as an alternative to our proposed ML estimator, it is shown that conventional GMM estimators based on standard orthogonality conditions break down if the underlying time series contain unit roots.Panel vector autoregressions, Fixed effects, Unit roots, Cointegration

The Cost Efficiency of UK Debt Management: A Recursive Modelling Approach

This paper presents an empirical analysis of the efficiency of the UK debt management authorities' (DMA) behaviour from a cost minimisation perspective over the period January 1985 to March 1995. During this period, the maturity structure of the government's bond portfolio was subject to frequent fine-tuning, aimed principally at lowering interest costs. The authors examine the efficiency of the DMA's behaviour from a cost minimisation perspective. Using a bi-variate version of the recursive modelling procedure applied to forecasting stock returns by Pesaran and Timmermann (1995, 2000), it is shown that bond returns are forecastable but that the predictive power of macroeconomic variables is time-dependent. The impact of adjusting the bond portfolio in response to these forecasts is simulated. The simulated average interest costs are lower than those resulting from the DMA's actual real-time behaviour. However, a substantial reduction in interest costs requires large monthly changes in the portfolio's maturity structure.Government debt management, Cost minimisation, Recursive modelling

Robust Standard Errors in Transformed Likelihood Estimation of Dynamic Panel Models

This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are crosssectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that arises, and its implications for estimation and inference. We approach the problem by working with a mis-specified homoskedastic model. It is shown that the transformed maximum likelihood estimator continues to be consistent even in the presence of cross-sectional heteroskedasticity. We also obtain standard errors that are robust to cross-sectional heteroskedasticity of unknown form. By means of Monte Carlo simulation, we investigate the finite sample behavior of the transformed maximum likelihood estimator and compare it with various GMM estimators proposed in the literature. Simulation results reveal that, in terms of median absolute errors and accuracy of inference, the transformed likelihood estimator outperforms the GMM estimators in almost all cases

One Hundred Years of Oil Income and the Iranian Economy: A curse or a Blessing

This paper examines the impact of oil revenues on the Iranian economy over the past hundred years, spanning the period 1908-2010. It is shown that although oil has been produced in Iran over a very long period, its importance in the Iranian economy was relatively small up until the early 1960s. It is argued that oil income has been both a blessing and a curse. Oil revenues when managed appropriately are a blessing, but their volatility (which in Iran is much higher than oil price volatility) can have adverse effects on real output, through excessively high and persistent levels of inflation. Lack of appropriate institutions and policy mechanisms which act as shock absorbers in the face of high levels of oil revenue volatility have also become a drag on real output. In order to promote growth, policies should be devised to control inflation; to serve as shock absorbers negating the adverse effects of oil revenue volatility; to reduce rent seeking activities; and to prevent excessive dependence of government finances on oil income

Identification of new Keynesian Phillips curves from a global perspective

This paper is concerned with the estimation of New Keynesian Phillips Curves (NKPC) and focuses on two issues: the weak instrument problem and the characterization of the steady states. It proposes some solutions from a global perspective. Using a global vector autoregressive (GVAR) model steady states are estimated as long-horizon expectations and valid instruments are constructed from the global variables as weighted averages. The proposed estimation strategy is illustrated using estimates of the NKPC for eight developed industrial countries. The GVAR generates global factors that are valid instruments and help alleviate the weak instrument problem. The steady states also reflect global influences and any long-run theoretical relationships that might prevail within and across countries in the global economy. The GVAR measure of the steady state performed better than the HP measure, and the use of foreign instruments substantially increased the precision of the estimates of the output coefficient

Supply, demand and monetary policy shocks in a multi-country new Keynesian model

This paper estimates and solves a multi-country version of the standard DSGE New Keynesian (NK) model. The country-specific models include a Phillips curve determining inflation, an IS curve determining output, a Taylor Rule determining interest rates, and a real effective exchange rate equation. The IS equation includes a real exchange rate variable and a countryspecific foreign output variable to capture direct inter-country linkages. In accord with the theory all variables are measured as deviations from their steady states, which are estimated as long-horizon forecasts from a reduced-form cointegrating global vector autoregression. The resulting rational expectations model is then estimated for 33 countries on data for 1980Q1-2006Q4, by inequality constrained IV, using lagged and contemporaneous foreign variables as instruments, subject to the restrictions implied by the NK theory. The multi-country DSGE NK model is then solved to provide estimates of identified supply, demand and monetary policy shocks. Following the literature, we assume that the within country supply, demand and monetary policy shocks are orthogonal, though shocks of the same type (e.g. supply shocks in different countries) can be correlated. We discuss estimation of impulse response functions and variance decompositions in such large systems, and present estimates allowing for both direct channels of international transmission through regression coefficients and indirect channels through error spillover effects. Bootstrapped error bands are also provided for the cross country responses of a shock to the US monetary policy

Counterfactual analysis in macroeconometrics: an empirical investigation into the effects of quantitative easing

The policy innovations that followed the recent Great Recession, such as unconventional monetary policies, prompted renewed interest in the question of how to measure the effectiveness of such policy interventions. To test policy effectiveness requires a model to construct a counterfactual for the outcome variable in the absence of the policy intervention and a way to determine whether the differences between the realised outcome and the model-based counter-factual outcomes are larger than what could have occurred by chance in the absence of policy intervention. Pesaran & Smith propose tests of policy ineffectiveness in the context of macroeconometric rational expectations dynamic stochastic general equilibrium models. When we are certain of the specification, estimation of the complete system imposing all the cross-equation restrictions implied by the full structural model is more efficient. But if the full model is misspecified, one may obtain more reliable estimates of the counterfactual outcomes from a parsimonious reduced form policy response equation, which conditions on lagged values, and on the policy measures and variables known to be invariant to the policy intervention. We propose policy ineffectiveness tests based on such reduced forms and illustrate the tests with an application to the unconventional monetary policy known as quantitative easing (QE) adopted in the UK

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 -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