|
on Forecasting |
| By: | Martin Feldkircher (Oesterreichische Nationalbank); Florian Huber (Oesterreichische Nationalbank); Josef Schreiner (Oesterreichische Nationalbank); Julia Woerz (Oesterreichische Nationalbank); Marcel Tirpak (National Bank of Slovakia, Research Department); Peter Toth (National Bank of Slovakia, Research Department) |
| Abstract: | In this article, we describe short-term forecasting models of economic activity for seven countries in Central, Eastern and Southeastern Europe (CESEE) and compare their forecasting performance since the outbreak of the Great Recession. To build these models, we use four variants of bridge equations and a dynamic factor model for each country. Given the differences in availability of monthly indicators across countries and the rather short time period over which these indicators are available, we favor smallscale forecasting models. We selected monthly indicators on the basis of expert judgment, correlation analysis and Bayesian model averaging techniques. While our odels generally outperform a purely time-series based forecast for all CESEE countries, there is no single technique that consistently produces the best out-of-sample forecast. To maximize forecasting accuracy, we therefore recommend selecting a country-specific suite of well-performing models for every CESEE economy. |
| Keywords: | Nowcasting, bridge equations, dynamic factor models, Bayesian model averaging,Central-, Eastern- and South-Eastern Europe |
| JEL: | C52 C53 E37 |
| Date: | 2015–06 |
| URL: | http://d.repec.org/n?u=RePEc:svk:wpaper:1033&r=for |
| By: | Mehmet Balcilar; Rangan Gupta (Department of Economics, Eastern Mediteranean University); Anandamayee Majumdar (Department of Finance, Grandiose University); Stephen Miller |
| Abstract: | This paper provides out-of-sample forecasts of Nevada gross gaming revenue and taxable sales using a battery of linear and non-linear forecasting models and univariate and multivariate techniques. The linear models include vector autoregressive and vector error-correction models with and without Bayesian priors. The non-linear models include non-parametric and semiparametric models, smooth transition autoregressive models and artificial neural network autoregressive models. In addition to gross gaming revenue and taxable sales, we employ recently constructed coincident and leading employment indexes for Nevada’s economy. We conclude that non-linear models generally outperform linear models in forecasting future movements in gross gaming revenue and taxable sales. |
| Keywords: | Forecasting, Linear and non-linear models, Nevada gross gaming revenue, Nevada taxable sales |
| JEL: | C32 R31 |
| URL: | http://d.repec.org/n?u=RePEc:emu:wpaper:dp15-01.pdf&r=for |
| By: | Marian Vavra (National Bank of Slovakia, Research Department) |
| Abstract: | This paper is concerned with the problem of testing for the equal forecast accuracy of competing models using a bootstrap-based Diebold-Mariano test statistic. The finite-sample properties of the test are assessed via Monte Carlo experiments. As an illustration, the forecast accuracy of the US Survey of Professional Forecasters is compared to that of an autoregressive model. The empirical results indicate that professionals beat AR models systematically only for a single economic variable – the unemployment rate |
| Keywords: | Forecast evaluation; Diebold-Mariano test; Sieve bootstrap |
| JEL: | C12 C15 C32 C53 |
| Date: | 2015–06 |
| URL: | http://d.repec.org/n?u=RePEc:svk:wpaper:1034&r=for |
| By: | Siem Jan Koopman (VU University Amsterdam); Rutger Lit (VU University Amsterdam); Andre Lucas (VU University Amsterdam) |
| Abstract: | We introduce a dynamic Skellam model that measures stochastic volatility from high-frequency tick-by-tick discrete stock price changes. The likelihood function for our model is analytically intractable and requires Monte Carlo integration methods for its numerical evaluation. The proposed methodology is applied to tick-by-tick data of four stocks traded on the New York Stock Exchange. We require fast simulation methods for likelihood evaluation since the number of observations per series per day varies from 1000 to 10,000. Complexities in the intraday dynamics of volatility and in the frequency of trades without price impact require further non-trivial adjustments to the dynamic Skellam model. In-sample residual diagnostics and goodness-of-fit statistics show that the final model provides a good fit to the data. An extensive forecasting study of intraday volatility shows that the dynamic modified Skellam model provides accurate forecasts compared to alternative modeling approaches. |
| Keywords: | non-Gaussian time series models; volatility models; importance sampling; numerical integration; high-frequency data; discrete price changes. |
| JEL: | C22 C32 C58 |
| Date: | 2015–07–01 |
| URL: | http://d.repec.org/n?u=RePEc:tin:wpaper:20150076&r=for |
| By: | Gilbert, Thomas (Foster School of Business); Scotti, Chiara (Board of Governors of the Federal Reserve System (U.S.)); Strasser, Georg (Boston College); Vega, Clara (Board of Governors of the Federal Reserve System (U.S.)) |
| Abstract: | The literature documents a heterogeneous asset price response to macroeconomic news announcements: Some announcements have a strong impact on asset prices and others do not. In order to explain these differences, we estimate a novel measure of the intrinsic value of a macroeconomic announcement, which we define as the announcement's ability to nowcast GDP growth, inflation, and the Federal Funds Target Rate. Using the same nowcasting framework, we then decompose this intrinsic value into the announcement's characteristics: its relation to fundamentals, timing, and revision noise. We find that in the 1998-2013 period, a significant fraction of the variation in the announcements' price impact on the Treasury bond futures market can be explained by differences in intrinsic value. Furthermore, our novel measure of timing explains significantly more of this variation than the announcements' relation to fundamentals, reporting lag (which previous studies have used as a measure of timing), or revision noise. |
| Keywords: | Macroeconomic announcements; central bank policy; coordination role of public information; learning; macroeconomic forecasting; price discovery |
| JEL: | E44 G14 |
| Date: | 2015–04–23 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fedgfe:2015-46&r=for |
| By: | Gauvin, Ludovic; Rebillard, Cyril |
| Abstract: | China’s rapid growth over the past decade has been one of the main drivers of the rise in mineral commodity demand and prices. At a time when concerns about the sustainability of China’s growth model are increasingly rising, this paper assesses to what extent a hard landing in China would impact commodity exporters. After reviewing the main arguments pointing to a hard landing scenario – historical rebalancing precedents, overinvestment, unsustainable debt trends, and a growing real estate bubble – we focus on a sample of twenty-five countries, and use a global VAR methodology adapted to conditional forecasting to simulate the impact of a Chinese hard landing. We model metal and oil price separately to account for their different end-use patterns and consumption intensity in China, and we identify two specific transmission channels to commodity exporters: through exports (with both volume and price effects), and through investment (a fall in commodity prices reducing incentives to invest in the mining sector). According to our estimates, Latin American countries would be hardest hit – with a 6 percent cumulated growth loss after five years – followed by Asia (ex. China); advanced economies would be less affected. The "growth gap" between emerging and advanced economies would be considerably reduced, leading to partial recoupling. |
| Keywords: | China; hard landing; spillovers; global VAR; conditional forecast; emerging economies; commodities; recoupling |
| JEL: | C32 E17 E32 F44 F47 Q02 |
| Date: | 2013–10 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:65457&r=for |
| By: | L. Gauvin; C. Rebillard |
| Abstract: | China’s rapid growth over the past decade has been one of the main drivers of the rise in mineral commodity demand and prices. At a time when concerns about the sustainability of China’s growth model are rising, this paper assesses to what extent a hard landing in China would impact other countries, with a focus on trade and commodity price channels. After reviewing the main arguments pointing to a hard landing scenario – historical rebalancing precedents, overinvestment, unsustainable debt trends, and a growing real estate bubble – we focus on a sample of thirty-six countries, and use a global VAR methodology adapted to conditional forecasting to simulate the impact of a Chinese hard landing. We model metal and oil markets separately to account for their different end-use patterns and consumption intensity in China, and we identify three specific transmission channels to net commodity exporters: through real exports, through income effects (related to commodity prices), and through investment (a fall in commodity prices reducing incentives to invest in the mining and energy sectors); we also look at the role played by the exchange rate as a shock absorber. According to our estimates, emerging economies (ex. China) would be hardest hit – with a 7.5 percent cumulated growth loss after five years –, in particular in South-East Asia but also in commodity-exporting regions such as Latin America; advanced economies would be less affected. The "growth gap" between emerging and advanced economies would be considerably reduced, leading to partial recoupling. |
| Keywords: | China, hard landing, spillovers, global VAR, conditional forecast, commodities, recoupling |
| JEL: | C32 F44 E32 E17 F47 Q02 |
| Date: | 2015 |
| URL: | http://d.repec.org/n?u=RePEc:bfr:banfra:562&r=for |
| By: | Luis Aguiar (European Commission - JRC - IPTS); Joel Waldfogel (University of Minnesota - Carlson School of Management) |
| Abstract: | We explore the consequence of quality unpredictability for the welfare benefit of new products, using recent developments in recorded music as our context. Digitization has expanded consumption opportunities by giving consumers access to the "long tail" of existing products, rather than simply the popular products that a retailer might stock with limited shelf space. While this is clearly beneficial to consumers, the benefits are somewhat limited: given the substitutability among differentiated products, the incremental benefit of obscure products - even lots of them - can be small. But digitization has also reduced the cost of bringing new products to market, giving rise to a different sort of long tail, in production. If the appeal of new products is unpredictable at the time of investment, as is the case for cultural products as well as many others, then creating new products can have substantial welfare benefits. Technological change in the recorded music industry tripled the number of new products between 2000 and 2008. We quantify the effects of new music on welfare using an explicit structural model of demand and entry with potentially unpredictable product quality. Based on plausible forecasting models of expected appeal, a tripling of the choice set according to expected quality adds more than fifteen times as much consumer surplus as the usual long-tail benefits from a tripling of the choice set according to realized quality. |
| Keywords: | music, Welfare, Entry, Digitization, Recorded Music |
| JEL: | D60 L13 L82 O33 |
| Date: | 2015–02 |
| URL: | http://d.repec.org/n?u=RePEc:ipt:decwpa:2015-02&r=for |