The present paper compares expected inflation to (econometric) inflation forecasts based on a number of forecasting techniques from the literature using a panel of ten industrialized countries during the period of 1988 to 2007. To capture expected inflation, we develop a recursive filtering algorithm which extracts unexpected inflation from real interest rate data, even in the presence of diverse risks and a potential Mundell-Tobin-effect. The extracted unexpected inflation is compared to the forecasting errors of ten econometric forecasts. Beside the standard AR(p) and ARMA(1,1) models, which are known to perform best on average, we also employ several Phillips curve based approaches, VAR, dynamic factor models and two simple model avering approaches.

Combining forecasts, we analyse the role of information flow in computing short-term forecasts up to one quarter ahead for the euro area GDP and its main components. A dataset of 114 monthly indicators is set up and simple bridge equations are estimated. The individual forecasts are then pooled, using different weighting schemes. To take into consideration the release calendar of each indicator, six forecasts are compiled successively during the quarter. We found that the sequencing of information determines the weight allocated to each block of indicators, especially when the first month of hard data becomes available. This conclusion extends the findings of the recent literature. Moreover, when combining forecasts, two weighting schemes are found to outperform the equal weighting scheme in almost all cases. Compared to an AR forecast, these improve by more than 40% the forecast performance for GDP in the current and next quarter.

Inflation and earnings growth can push some tax payers into higher brackets in the absence of inflation-indexed schedules. Moreover, inflation may affect the composition of individuals’ income sources. As a result, depending on the relative tax burden of labour and capital, inflation may decrease or increase the difference between before-tax and after-tax income. However, whether some and if so which percentiles of the income distribution net benefit from inflation via taxation is a widely unexplored question. We make use of a novel dataset on U.S. pre-tax and post-tax income distribution series provided by Pike ty et al. (2018) for the years 1962 to 2014 to answer this question. To this end, we estimate local projections to quantify dynamic effects. We find that inflation shocks increase progressivity of taxation not only contemporaneously but also with some repercussion of several years after the shock. While particularly the bottom two quintiles gain in share, it is not the top but the fourth quintile that lastingly loses.

This study analyzes the performance of the IMF World Economic Outlook forecasts for world output and the aggregates of both the advanced economies and the emerging and developing economies. With a focus on the forecast for the current and the next year, we examine whether IMF forecasts can be improved by using leading indicators with monthly updates. Using a real-time dataset for GDP and for the indicators we find that some simple single-indicator forecasts on the basis of data that are available at higher frequency can significantly outperform the IMF forecasts if the publication of the Outlook is only a few months old.

Many economic decisions implicitly or explicitly rely on a projection of the medium- or long-term economic development of a country or region. In this paper, we provide a federal long-run projection model for Germany and the German states. The model fea-tures a top-down approach and, as major contribution, uses error correction models to estimate the regional economic development dependent on the national projection. For the medium- and long-term projection of economic activity, we apply a production function approach. We provide a detailed robustness analysis by systematically varying assumptions of the model. Additionally, we explore the effects of different demographic trends on economic development.

In the tradition of Romer and Romer (2000), this paper compares staff forecasts of the Federal Reserve (Fed) and the European Central Bank (ECB) for inflation and output with corresponding private forecasts. Standard tests show that the Fed and less so the ECB have a considerable information advantage about inflation and output. Using novel tests for conditional predictive ability and forecast stability for the US, we identify the driving forces of the narrowing of the information advantage of Greenbook forecasts coinciding with the Great Moderation.

This paper assesses whether the economy of East Germany is catching up with the West German region in terms of welfare. While the primary measure for convergence and catching up is per capita output, we also look at other macroeconomic indicators such as unemployment rates, wage rates, and production levels in the manufacturingsector. In contrast to existing studies of convergence between regions of reunified Germany, our approach is purely based upon the time series dimension and is thus directly focused on the catching up process in East Germany as a region. Our testing setup includes standard ADF unit root tests as well as unit root tests that endogenously allow for a break in the deterministic component of the process. In our analysis, we find evidence of catching up for East Germany for most of the indicators. However, convergence speed is slow, and thus it can be expected that the catching up process will take further decades until the regional gap is closed.