A new sectoral unit labour cost indicator based on global value chains

Autor: Martyna Marczak, Thomas Beissinger

Publikováno v: Applied Economics Letters. 29:1152-1157

We propose ‘embodied unit labour costs’ (EULC) at the country-sector level as a new cost-related competitiveness indicator. EULC are more comprehensive than standard unit labour cost measures as th...

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::3ffbbbc3ef0361ccc7ac5b954bcdb60a
https://doi.org/10.1080/13504851.2021.1915461

Divergence in Labour Force Growth: Should Wages and Prices Grow Faster in Germany?

Autor: Thomas Beissinger, Joël Hellier, Martyna Marczak

Publikováno v: SSRN Electronic Journal.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a61d9934fe7d78df77b451300e3eadec
https://doi.org/10.2139/ssrn.3665098

A class of periodic trend models for seasonal time series

Autor: Gianluigi Mazzi, Martyna Marczak, Tommaso Proietti

Publikováno v: Proietti, T, Marczak, M & Mazzi, G 2019, ' A class of periodic trend models for seasonal time series ', Journal of Forecasting, vol. 38, no. 2, pp. 106-121 . https://doi.org/10.1002/for.2562

Trend and seasonality are the most prominent features of economic time series that are observed at the subannual frequency. Modeling these components serves a variety of analytical purposes, including seasonal adjustment and forecasting. In this pape

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e5b98f8849047b3c327b8e936c21fa2a
https://pure.au.dk/portal/da/publications/a-class-of-periodic-trend-models-for-seasonal-time-series(24cc83ee-dff9-4775-9088-e8e870a174d7).html

Competitiveness at the Country-Sector Level: New Measures Based on Global Value Chains

Autor: Martyna Marczak, Thomas Beissinger

Publikováno v: SSRN Electronic Journal.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::a93cda1c60d2bd5856fb4fbf00a9b1fb
https://doi.org/10.2139/ssrn.3177374

A Data-Cleaning Augmented Kalman Filter for Robust Estimation of State Space Models

Autor: Stefano Grassi, Martyna Marczak, Tommaso Proietti

Publikováno v: Marczak, M, Proietti, T & Grassi, S 2018, ' A data-cleaning augmented Kalman filter for robust estimation of state space models ', Econometrics and Statistics, vol. 5, no. 1, pp. 107-123 . https://doi.org/10.1016/j.ecosta.2017.02.002

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 t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::792c86f634f8db18ee170fd88b01cbde
https://doi.org/10.2139/ssrn.2756074