Testing a Simple Structural Model of Endogenous Growth

The efect of taxation on growth is embodied in a model of a small open economy with endogenous growth. The structural model is estimated on post-war panel data for 76 countries and the bootstrap is used to produce the model’s sampling variation. Panel data regressions of growth on taxation do not reject this model but do reject a model with no tax effects.endogenous growth, taxation, business regulation, bootstrap, model validation.

Testing a DSGE model of the EU using indirect inference

We use the method of indirect inference, using the bootstrap, to test the Smets and Wouters model of the EU against a VAR auxiliary equation describing their data; the test is based on the Wald statistic. We find that their model generates excessive variance compared with the data. If the errors are scaled down, then the original model marginally passes the Wald test. We compare a New Classical version of the model which passes the test but generates a combination of excessive inflation variance and inadequate output variance. If the large consumption and investment errors are removed as possibly due to low frequency events, then the New Classical version passes easily while the original version is strongly rejected.Bootstrap, DSGE Model, VAR model, Model of EU, indirect inference, Wald statistic.

Testing a DSGE model of the EU using indirect inference

We use the method of indirect inference, using the bootstrap, to test the Smets and Wouters model of the EU against a VAR auxiliary equation describing their data; the test is based on the Wald statistic. We find that their model generates excessive variance compared with the data. But their model passes the Wald test easily if the errors have the properties assumed by SW but scaled down. We compare a New Classical version of the model which also passes the test easily if error properties are chosen using New Classical priors (notably excluding shocks to preferences). Both versions have (different) difficulties fitting the data if the actual error properties are used.Bootstrap, DSGE Model, VAR model, Model of EU, indirect inference, Wald statistic.

Two orthogonal continents: Testing a two-country DSGE model of the US and the EU using indirect inference

We examine a two country model of the EU and the US. Each has a small sector of the labour and product markets in which there is wage/price rigidity, but otherwise enjoys flexible wages and prices with a one quarter information lag. Using a VAR to represent the data, we find the model as a whole is rejected. However it is accepted for real variables, output and the real exchange rate, suggesting mis-specification lies in monetary relationships. The model highlights a lack of spillovers between the US and the EU

Testing a model of the UK by the method of indirect inference

We use the method of indirect inference to test a full open economy model of the UK that has been in forecasting use for three decades. The test establishes, using a Wald statistic, whether the parameters of a time-series representation estimated on the actual data lie within some confidence interval of the model-implied distribution. Various forms of time-series representations that could deal with the UK's various changes of monetary regime are tried; two are retained as adequate. The model is rejected under one but marginally accepted under the other, suggesting that with some modifications it could achieve general acceptability and that the testing method is worth investigating further

Testing and estimating models using indirect inference

In this short article we explain how to test an economic model using Indirect Inference. We then go on to show how you can use this test to estimate the model

Testing macroeconomic models by indirect inference on unfiltered data

We extend the method of indirect inference testing to data that is not filtered and so may be non-stationary. We apply the method to an open economy real business cycle model on UK data. We review the method using a Monte Carlo experiment and find that it performs accurately and has good power

Can a Real Business Cycle Model without price and wage stickiness explain UK real exchange rate behaviour?

This paper establishes the ability of a Real Business Cycle model to account for real exchange rate behaviour, using UK data. We show that a productivity simulation is capable of explaining initial real appreciation with subsequent depreciation to a lower steady state. The model is tested by the method of indirect inference, bootstrapping the errors to generate 95% confidence limits for a time-series representation of the real exchange rate, as well as for various key data moments. The results suggest RBC models can explain real exchange rate movements

What causes banking crises? An empirical investigation

We add the Bernanke-Gertler-Gilchrist model to a modified version of the Smets-Wouters model of the US in order to explore the causes of the banking crisis. We test the model against the data on HP-detrended data and reestimate it by indirect inference; the resulting model passes the Wald test on output, inflation and interest rates. We then extract the model's implied residuals on US unfiltered data since 1984 to replicate how the model predicts the crisis. The main banking shock tracks the unfolding 'sub-prime' shock, which appears to have been authored mainly by US government intervention. This shock worsens the banking crisis but 'traditional' shocks explain the bulk of the crisis; the non-stationarity of the productivity shock plays a key role. Crises occur when there is a 'run' of bad shocks; based on this sample they occur on average once every 40 years and when they occur around half are accompanied by financial crisis. Financial shocks on their own, even when extreme, do not cause crises - provided the government acts swiftly to counteract such a shock as happened in this sample

Comparing Indirect Inference and likelihood testing: Asymptotic and small sample results

Indirect Inference has been found to have much greater power than the Likelihood Ratio in small samples for testing DSGE models. We look at asymptotic and large sample properties of these tests to understand why this might be the case. We find that the power of the LR test is undermined when reestimation of the error parameters is permitted; this offsets the effect of the falseness of structural parameters on the overall forecast error. Even when the two tests are done on a like-for-like basis Indirect Inference has more power because it uses the distribution restricted by the DSGE model being tested