A Comparison Of Forecasting Procedures For Macroeconomic Series: The Contribution Of Structural Break Models

This paper compares the forecasting performance of different models which have been proposed for forecasting in the presence of structural breaks. These models differ in their treatment of the break process, the parameters defining the model which applies in each regime and the out-of-sample probability of a break occurring. In an extensive empirical evaluation involving many important macroeconomic time series, we demonstrate the presence of structural breaks and their importance for forecasting in the vast majority of cases. However, we find no single forecasting model consistently works best in the presence of structural breaks. In many cases, the formal modeling of the break process is important in achieving good forecast performance. However, there are also many cases where simple, rolling OLS forecasts perform well.

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.

Productivity shocks and aggregate fluctuations in an estimated endogenous growth model with human capital

Employing an endogenous growth model with human capital, this paper explores how productivity shocks in the goods and human capital producing sectors contribute to explaining aggregate fluctuations in output, consumption, investment and hours. Given the importance of accounting for both the dynamics and the trends in the data not captured by the theoretical growth model, we introduce a vector error correction model (VECM) of the measurement errors and estimate the model’s posterior density function using Bayesian methods. To contextualize our findings with those in the literature, we also assess whether the endogenous growth model or the standard real business cycle model better explains the observed variation in these aggregates. In addressing these issues we contribute to both the methods of analysis and the ongoing debate regarding the effects of innovations to productivity on macroeconomic activity.

The Technological Specialization of Countries: An Analysis of Patent Data

New methods of analysis of patent statistics allow assessing country profiles of technological specialization for the period 1990-2006. We witness a modest decrease in levels of specialization, which we show to be negatively influenced by country size and degree of internationalization of inventive activities.

Cyclical and Welfare Effects of Public Sector Unions in a Real-Business-Cycle Model

Motivated by the highly-unionized public sectors, the high public shares in total employment, and the public sector wage premia observed in Europe, this paper examines the importance of public sector unions for macroeconomic theory. The model generates cyclical behavior in hours and wages that is consistent with data behavior in an economy with highly-unionized public sector, namely Germany during the period 1970-2007. The union model is a signifi cant improvement over a model with exogenous public employment. In addition, endogenously-determined public wage and hours add to the distortionary e ffect of contractionary tax reforms by generating greater tax rate changes, thus producing signi ficantly higher welfare losses.

Currency Forecast Errors at Times of Low Interest Rates: Evidence from Survey Data on the Yen/Dollar Exchange Rate

Using survey expectations data and Markov-switching models, this paper evaluates the characteristics and evolution of investors' forecast errors about the yen/dollar exchange rate. Since our model is derived from the uncovered interest rate parity (UIRP) condition and our data cover a period of low interest rates, this study is also related to the forward premium puzzle and the currency carry trade strategy. We obtain the following results. First, with the same forecast horizon, exchange rate forecasts are homogeneous among different industry types, but within the same industry, exchange rate forecasts differ if the forecast time horizon is different. In particular, investors tend to undervalue the future exchange rate for long term forecast horizons; however, in the short run they tend to overvalue the future exchange rate. Second, while forecast errors are found to be partly driven by interest rate spreads, evidence against the UIRP is provided regardless of the forecasting time horizon; the forward premium puzzle becomes more significant in shorter term forecasting errors. Consistent with this finding, our coefficients on interest rate spreads provide indirect evidence of the yen carry trade over only a short term forecast horizon. Furthermore, the carry trade seems to be active when there is a clear indication that the interest rate will be low in the future.

Macroeconomics: Science or Faith Based Discipline?

Whether or not macroeconomics is a science depends on the scientific nature of macroeconomic theories and how the discipline responds when the empirical evidence fails to match the underlying assumptions and predictions of the theories. By way of an example, four conditions for macroeconomics to be a science are developed and used to examine the 'modern' theories of the Phillips curve. It is found that while the discipline in general maintains one condition it routinely violates the other three. This suggests the macroeconomics discipline has some way to go before it can call itself a 'pure science.'

Empirical testing of genuine savings as an indicator of weak sustainability: a three-country analysis of long run trends

Genuine Savings has emerged as a widely-used indicator of sustainable development. In this paper, we use long-term data stretching back to 1870 to undertake empirical tests of the relationship between Genuine Savings (GS) and future well-being for three countries: Britain, the USA and Germany. Our tests are based on an underlying theoretical relationship between GS and changes in the present value of future consumption. Based on both single country and panel results, we find evidence supporting the existence of a cointegrating (long run equilibrium) relationship between GS and future well-being, and fail to reject the basic theoretical result on the relationship between these two macroeconomic variables. This provides some support for the GS measure of weak sustainability. We also show the effects of modelling shocks, such as World War Two and the Great Depression.

Data-based priors for vector autoregressions with drifting coefficients

This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require minimal input by the user, and they result in shrinkage posterior representations, thus, making them appropriate for models of large dimensions. A comprehensive forecasting exercise involving TVP-VARs of different dimensions establishes the usefulness of the proposed approach.

Nowcasting Scottish GDP Growth

The delays in the release of macroeconomic variables such as GDP mean that policymakers do not know their current values. Thus, nowcasts, which are estimates of current values of macroeconomic variables, are becoming increasingly popular. This paper takes up the challenge of nowcasting Scottish GDP growth. Nowcasting in Scotland, currently a government office region within the United Kingdom, is complicated due to data limitations. For instance, key nowcast predictors such as industrial production are unavailable. Accordingly, we use data on some non-traditional variables and investigate whether UK aggregates can help nowcast Scottish GDP growth. Such data limitations are shared by many other sub-national regions, so we hope this paper can provide lessons for other regions interested in developing nowcasting models.

Human Capital in Economic Development: From Labour Productivity to Macroeconomic Impact

Micro-econometric evidence reveals high private returns to education, most prominently in low-income countries. However, it is disputed to what extent this translates into a macro-economic impact. This paper projects the increase in human capital from higher education in Malawi and uses a dynamic applied general equilibrium model to estimate the resulting macroeconomics impact. This is contingent upon endogenous adjustments, in particular how labour productivity affects competitiveness and if this in turn stimulates exports. Choice among commonly applied labour market assumptions and trade elasticities results in widely different outcomes. Appraisal of such policies should consider not only the impact on human capital stocks, but also adjustments outside the labour market.