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2017 | 1 | 327 |

Article title

Przestrzenne podejście do analizy międzysektorowej mobilności płac oraz zatrudnienia

Content

Title variants

Przestrzenne podejście do analizy międzysektorowej mobilności płac oraz zatrudnienia

Languages of publication

PL

Abstracts

PL
Głównym celem opracowania jest przedstawienie możliwości zastosowania macierzy sąsiedztwa, opartej na odległości ekonomicznej, w prowadzonych przez autora analizach wiążących międzysektorową mobilność płac oraz zatrudnienia. Obliczenia odległości ekonomicznej oparto na poziomie PKB, natomiast w modelu przestrzennym wykorzystano dane dotyczące ich wybranych determinant, np. wskaźnika nierówności płacowych, przeciętnego poziomu płac, stopy bezrobocia, miernika instytucjonalizmu. Przekrój czasowy analizy uzyskano dzięki zastosowaniu mierników mobilności bazujących na macierzy prawdopodobieństw przejść oszacowanych z użyciem procesów Markowa dla danych zagregowanych. Z uwagi na dostępność jednorodnych, wysoce zagregowanych (do poziomu sektora) danych jedynie dla lat 1994–2010 ograniczono się do przeprowadzenia analizy wyłącznie dla 19 wybranych krajów OECD.
EN
The article presents the problem of the application of spatial weight matrix based on economic distance in spatial analysis of the intersectoral mobility of labor and wage. The spatial weight matrix expresses potential spatial interactions between the researched regions and forms a basis for further construction of spatial econometric model. Calculations of economic distance were based on the level of chosen measure of labor or wage mobility (respectively), whereas in the spatial model data of their chosen determinants were used (such as the level of unemployment, the average earnings, the level of institutionalism, the index of wage or income inequality). Wide time spectrum of the analysis was obtained thanks to the measure of mobility based on a transition probability matrix estimated with the use of the analysis of Markov processes for aggregated data. Because of the availability of homogeneous, highly aggregated sectoral data only for the period 1994–2010, the analyses were performed for 19 selected OECD countries.

Year

Volume

1

Issue

327

Physical description

Dates

published
2017-07-11

Contributors

  • Gdańsk University of Technology, Faculty of Management and Economics, Department of Economic Sciences

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Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.ojs-doi-10_18778_0208-6018_327_08
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