Browsing by Person "Marczak, Martyna"

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A data–cleaning augmented Kalman filter for robust estimation of state space models
(2015) Marczak, Martyna; Proietti, Tommaso; Grassi, Stefano
This article presents a robust augmented Kalman filter that extends the data– cleaning filter (Masreliez and Martin, 1977) to the general state space model featuring nonstationary and regression effects. The robust filter shrinks the observations towards their one–step–ahead prediction based on the past, by bounding the effect of the information carried by a new observation according to an influence function. When maximum likelihood estimation is carried out on the replacement data, an M–type estimator is obtained. We investigate the performance of the robust AKF in two applications using as a modeling framework the basic structural time series model, a popular unobserved components model in the analysis of seasonal time series. First, a Monte Carlo experiment is conducted in order to evaluate the com- parative accuracy of the proposed method for estimating the variance parameters. Second, the method is applied in a forecasting context to a large set of European trade statistics series.
Bidirectional relationship between investor sentiment and excessreturns : new evidence from the wavelet perspective
(2015) Marczak, Martyna; Beißinger, Thomas
This paper sheds new light on the mutual relationship between investor sentiment and excess returns corresponding to the bubble component of stock prices. We propose to use the wavelet concept of the phase angle to determine the lead–lag relation between these variables. The wavelet phase angle allows for decoupling short– and long–run relations and is additionally capable of identifying time–varying comovement patterns. By applying this concept to excess returns of the monthly S&P500 index and two alternative monthly US sentiment indicators we find that in the short run (until 3 months) sentiment is leading returns whereas for periods above 3 months the opposite can be observed.
Competitiveness at the country-sector level : new measures based on global value chains
(2018) Beißinger, Thomas; Marczak, Martyna
We propose the so-called domestic “embodied unit labor costs” (EULC) at the country-sector level as a new cost-related basis for measures of international competitiveness. EULC take into account that a sector’s labor costs constitute only a small share of its total cost which to a large extent consist of expenses for inter- mediate goods from other sectors. In line with a simple Leontief-type model, the proposed measure is constructed as a weighted average of unit labor costs of all do- mestic sectors contributing to the final goods of a specific sector. The contribution is expressed in value-added terms and takes global supply chains into account. We also show how EULC can be consistently calculated for sectoral aggregates such as the tradable goods sector. Based on EULC we propose the “embodied real effec- tive exchange rate” (EREER) at the country-sector level as a new competitiveness indicator where the relevance of trading partners is quantified by an appropriate value-added measure. The chosen value-added concept replaces gross exports tra- ditionally used as the weight basis in effective exchange rates. Using the World Input-Output Database (WIOD) we employ the proposed indicators to shed new light on changes in cost competitiveness at the sectoral level for Germany, and compare the empirical evidence with selected other euro area countries.
Cyclicality of real wages in the USA and Germany : new insights from wavelet Analysis
(2012) Gómez, Víctor ; Marczak, Martyna
This article provides new insights into the cyclical behavior of consumer and producer real wages in the USA and Germany. We apply two methods for the estimation of the cyclical components from the data: the approach based on the structural time series models and the ARIMA?model?based approach combined with the canonical decomposition and a band?pass filter. We examine the extracted cycles drawing on two wavelet concepts: wavelet coherence and wavelet phase angle. In contrast to the analysis in the time or frequency domains, wavelet analysis allows for the identification of possible changes in cyclical patterns over time. From the findings of our study, we can infer that the USA and Germany differ with respect to the lead?lag relationship of real wages and the business cycle. In the USA, both real wages are leading the business cycle in the entire time interval. The German consumer real wage is, on the other hand, lagging the business cycle. For the German producer real wage, the lead?lag pattern changes over time. We also find that real wages in the USA as well in Germany are procyclical or acyclical until 1980 and countercyclical thereafter.
Divergence in labour force growth : should wages and prices grow faster in Germany?
(2020) Marczak, Martyna; Hellier, Joël; Beißinger, Thomas
We develop a model which shows that wages, prices and real income should grow faster in countries with low increase in their labour force. If not, other countries experience growing unemployment and/or trade deficit. This result is applied to the case of Germany, which has displayed a significantly lower increase in its labour force than its trade partners, except in the moment of the reunification. By assuming that goods are differentiated according to their country of origin (Armington’s hypothesis), a low growth of the working population constrains the production of German goods, which entails an increase in their prices and in German wages. This mechanism is magnified by the low price elasticity of the demand for German goods.Hence,the German policy of wage moderation could severely constrain other countries’ policy options. The simulations of an extended model which encompasses offshoring to emerging countries and labour market imperfections suggest that (i) the impact of differences in labour force growth upon unemployment in Eurozone countries has been significant and (ii) the German demographic shock following unification could explain a large part of the 1995-2005 German economic turmoil.
EuroMInd-D : a density estimate of monthly gross domestic product for the Euro area
(2015) Proietti, Tommaso; Marczak, Martyna; Mazzi, Gianluigi
EuroMInd-D is a density estimate of monthly gross domestic product (GDP) constructed according to a bottom–up approach, pooling the density estimates of eleven GDP components, by output and expenditure type. The components density estimates are obtained from a medium-size dynamic factor model of a set of coincident time series handling mixed frequencies of observation and ragged–edged data structures. They reflect both parameter and filtering uncertainty and are obtained by implementing a bootstrap algorithm for simulating from the distribution of the maximum likelihood estimators of the model parameters, and conditional simulation filters for simulating from the predictive distribution of GDP. Both algorithms process sequentially the data as they become available in real time. The GDP density estimates for the output and expenditure approach are combined using alternative weighting schemes and evaluated with different tests based on the probability integral transform and by applying scoring rules.
Four essays in the empirical analysis of business cycles and structural breaks
(2015) Marczak, Martyna; Beißinger, Thomas
Business cycle analysis has a long history in the macroeconomics literature and since its origins it poses a challenge for both empirical and theoretical research. The enduring interest in this research area is dictated by its high relevance for economic policy. Reliable information on the state of the economy plays a crucial role in the monitoring of the economy and in the policy-making process. This involves the choice of the method for extraction of a proper business cycle indicator. Moreover, the business cycle analyst also has to take account of structural breaks as well as seasonal and higher frequency movements of the series that can affect the properties of a business cycle indicator. Another reason for the keen interest in empirical business cycle research can be seen in the need to validate theoretical approaches. A prominent example is the debate on the cyclical behavior of real wages which evolved to one of the most lively and long--lasting debates in macroeconomics. This thesis tries to contribute to the literature under the aforementioned aspects. It offers a new methodological perspective with respect to the extraction of business cycles and detection of structural breaks. Furthermore, it sheds some light on the question of real wage cyclicality from the empirical point of view. The first essay proposes a new multivariate model based on a band-pass filter to construct business cycle indicators. Using this method and a dataset with monthly and quarterly US time series, two monthly business cycle indicators are obtained for the US. It is shown that the proposed method not only reproduces historical recessions very well, but it also performs good in terms of forecasting. The second essay for the first time in the literature combines indicator saturation as a general-to-specific approach to detect outliers and structural breaks with the structural time series model for the purpose of seasonal adjustment. The performance of the impulse-indicator and step-indicator saturation for detecting additive outliers and level shifts is tested in both a comprehensive Monte Carlo simulation exercise and an empirical application. The latter involves five European industrial production series. Its focus lies on the question whether the recessionary episode starting towards the end of 2008 can be described by the inherent model dynamics, or whether it represents a major structural change. In the third essay, stylized facts about the cyclicality of real consumer wages and real producer wages in Germany are established. First, various detrending methods are applied to estimate a business cycle and real wage cycles. The comovements between real wage cycles and the business cycle are then examined both in the time domain and in the frequency domain by resorting to the concept of the phase angle. According to the frequency domain results, the consumer real wage lags behind the business cycle. Moreover, it exhibits an anticyclical behavior in the short run, whereas in the longer run a procyclical behavior can be observed. For the producer real wage, in contrast, the results in the frequency domain are not clear-cut. The fourth essay compares the cyclical behavior of consumer and producer real wages in the USA and Germany. This study is the first one which employs wavelet analysis as a comovement tool in the context of the examined research question. From the findings of this study it can be inferred that the USA and Germany differ with respect to the lead-lag relationship of real wages and the business cycle. In the USA, both real wages are leading the business cycle in the entire time interval. The German consumer real wage is, on the other hand, lagging the business cycle. For the German producer real wage, the lead-lag pattern changes over time. In addition, the results show that real wages in the USA as well in Germany are procyclical or acyclical until 1980 and countercyclical thereafter.
Illuminating the World Cup effect : night lights evidence from South Africa
(2016) Pfeifer, Gregor; Wahl, Fabian; Marczak, Martyna
This paper evaluates the economic impact of the $14 billion preparatory investments for the 2010 FIFA World Cup in South Africa. We use satellite data on night light luminosity at municipality and electoral district level as a proxy for economic development, applying synthetic control methods for estimation. For the average World Cup municipality, we find significantly positive, short-run effects before the tournament, corresponding to a reduction of unemployment by 1.3 percentage points. At the electoral district level, we reveal distinct effect heterogeneity, where especially investments in transport infrastructure are shown to have long-lasting, positive effects, particularly in more rural areas.
Monthly US business cycle indicators : a new multivariate approach based on a band-pass filter
(2013) Gómez, Víctor; Marczak, Martyna
This article proposes a new multivariate method to construct business cycle indicators. The method is based on a decomposition into trend-cycle and irregular. To derive the cycle, a multivariate band-pass filter is applied to the estimated trend-cycle. The whole procedure is fully model-based. Using a set of monthly and quarterly US time series, two monthly business cycle indicators are obtained for the US. They are represented by the smoothed cycles of real GDP and the industrial production index. Both indicators are able to reproduce previous recessions very well. Series contributing to the construction of both indicators are allowed to be leading, lagging or coincident relative to the business cycle. Their behavior is assessed by means of the phase angle and the mean phase angle after cycle estimation. The proposed multivariate method can serve as an attractive tool for policy making, in particular due to its good forecasting performance and quite simple setting. The model ensures reliable realtime forecasts even though it does not involve elaborate mechanisms that account for, e.g., changes in volatility.
Outlier detection in structural time series models : the indicator saturation approach
(2014) Proietti, Tommaso; Marczak, Martyna
Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has attracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The general–to–specific approach to the detection of structural change, currently implemented in Autometrics via indicator saturation, has proven to be both practical and effective in the context of stationary dynamic regression models and unit–root autoregressions. By focusing on impulse– and step–indicator saturation, we investigate via Monte Carlo simulations how this approach performs for detecting additive outliers and level shifts in the analysis of nonstationary seasonal time series. The reference model is the basic structural model, featuring a local linear trend, possibly integrated of order two, stochastic seasonality and a stationary component. Further, we apply both kinds of indicator saturation to detect additive outliers and level shifts in the industrial production series in five European countries.
Real wages and the business cycle in Germany
(2010) Beißinger, Thomas; Marczak, Martyna
This paper establishes stylized facts about the cyclicality of real consumer wages and real producer wages in Germany. As detrending methods we apply the deterministic trend model, the Beveridge-Nelson decomposition, the Hodrick-Prescott filter, the Baxter-King filter and the structural time series model. The detrended data are analyzed both in the time domain and in the frequency domain. The great advantage of an analysis in the frequency domain is that it allows to assess the relative importance of particular frequencies for the behavior of real wages. In the time domain we find that both real wages display a procyclical pattern and lag behind the business cycle. In the frequency domain the consumer real wage lags behind the business cycle and shows an anticyclical behavior for shorter time periods, whereas for longer time spans a procyclical behavior can be observed. However, for the producer real wage the results in the frequency domain remain inconclusive.
SPECTRAN, a set of Matlab programs for spectral analysis
(2012) Marczak, Martyna; Gómez, Víctor
Spectral analysis is one of the most important areas of time series econometrics. The use of spectral measures is widespread in different science fields such as economics, physics, engineering, geology. The SPECTRAN toolbox has been developed to facilitate the application of spectral concepts to univariate as well as to multivariate series. It offers a variety of frequency-domain techniques and supports the statistical inference. It also provides convenient tools for the examination of the results, e.g.functions for writing the output to a file or functions specially designed for plotting the estimated spectral measures. The key feature of SPECTRAN is the user-friendliness embodied in, e.g., the central function spectran which performs the whole analysis with default settings, but also gives the user the possibility to adjust them. This document sets out the most relevant spectral concepts and their implementation in SPECTRAN. Finally, three examples shall illustrate the application of different toolbox function to macroeconomic data.
Technical change, task allocation, and labor unions
(2022) Marczak, Martyna; Beißinger, Thomas; Brall, Franziska
We propose a novel framework that integrates the task approach" for a more precise production modeling into the search-and-matching model with low- and high-skilled workers, and wage setting by labor unions. We establish the relationship between task reallocation and changes in wage pressure, and examine how skill- biased technical change (SBTC) affects the task composition, wages of both skill groups, and unemployment. In contrast to the canonical model with a fixed task allocation, low-skilled workers may be harmed in terms of either lower wages or higher unemployment depending on the relative task-related productivity profile of both worker types. We calibrate the model to the US and German data for the periods 1995-2005 and 2010-2017. The simulated effects of SBTC on low-skilled unemployment are largely consistent with observed developments. For example, US low-skilled unemployment increases due to SBTC in the earlier period and decreases after 2010.