STILL ‘FEW, SLOW AND LOW’? ON THE FEMALE DIMENSION OF TECHNOLOGY, LABOUR MARKETS AND ECONOMIC ACTIVITY: EVIDENCE FOR THE PERIOD OF 1990-2017 - Publication - Bridge of Knowledge

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STILL ‘FEW, SLOW AND LOW’? ON THE FEMALE DIMENSION OF TECHNOLOGY, LABOUR MARKETS AND ECONOMIC ACTIVITY: EVIDENCE FOR THE PERIOD OF 1990-2017

Abstract

The known in empirical economics question ‘Why so Few? Why so Slow? Why so Low?’ refers here to the persistently small number of women involved in innovative activities, the slowness of change in the inequalities between women and men in these fields, and women’s continuing lower rank in business and academic positions. In developing countries, women`s labour and entrepreneurial activity remains an ‘untapped resource’ for economic growth. In recent years, the rising proportion of women participating in the labour market has drawn the attention of many scholars. This positive change towards mobilising previously unused human resources is perceived as one of the positive externalities enhanced by the seemingly boundless flow of information and communication technology. This research examines, from a macroperspective, the association between economic deployment of ICT, women`s labour market participation, and economic growth in 64 developing countries between 1990 and 2017. We rely on the macrodata extracted from the World Bank Development Indicators (2018), the World Bank Enterprise Survey, the World Development Reports and the World Telecommunication/ICT Indicators Database (2018). Our methodological framework, in addition to standard descriptive statistics, combines time trends, graphical non-parametric analysis and panel vector-autoregressive models.

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Category:
Articles
Type:
artykuły w czasopismach recenzowanych i innych wydawnictwach ciągłych
Published in:
Economics & Sociology no. 12, pages 11 - 38,
ISSN: 2071-789X
Language:
English
Publication year:
2019
Bibliographic description:
Lechman E.: STILL ‘FEW, SLOW AND LOW’? ON THE FEMALE DIMENSION OF TECHNOLOGY, LABOUR MARKETS AND ECONOMIC ACTIVITY: EVIDENCE FOR THE PERIOD OF 1990-2017// Economics&Sociology. -Vol. 12., iss. 1 (2019), s.11-38
DOI:
Digital Object Identifier (open in new tab) 10.14254/2071-789x.2019/12-1/1
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  1. Abrigo, M. R. & Love, I. (2016). Estimation of panel vector autoregression in Stata. Stata Journal, 16(3), 778-804. open in new tab
  2. Abrigo, M. R., & Love, I. (2016a). Estimation of panel vector autoregression in stata: A package of programs. University of Hawaii. Working paper, (16-2). open in new tab
  3. Afrah, S. H. & Fabiha, S. T. (2017). Empowering Women Entrepreneurs through Information and Communication Technology (ICT): A Case Study of Bangladesh. Management, 7(1), 1-6.
  4. Afshar, H. (Ed.). (2016). Women and empowerment: Illustrations from the Third World. Springer.
  5. Akaike, H. (1969). Fitting autoregressive models for prediction. Annals of the Institute of Statistical Mathematics, 21(1), 243-247. open in new tab
  6. Akaike, H. (1977). On entropy maximization principle, in P. R. Krishnaiah, (ed.) Applications of Statistics. Amsterdam: North-Holland, pp. 27-41.
  7. Aknouche, A. (2007). Causality conditions and autocovariance calculations in PVAR models. Journal of Statistical Computation and Simulation, 77(9), 769-780. open in new tab
  8. Allen, S. & Truman, C. (2016). Women in business: Perspectives on women entrepreneurs. Routledge. open in new tab
  9. Amisano, G., & Geweke, J. (2017). Prediction using several macroeconomic models. Review of Economics and Statistics, 99(5), 912-925. open in new tab
  10. Anderson, T. W. & Hsiao, C. (1982). Formulation and estimation of dynamic models using panel data. Journal of Econometrics, 18(1), 47-82. open in new tab
  11. Andersson, A. & Hatakka, M. (2017). Victim, Mother, or Untapped Resource? Discourse Analysis of the Construction of Women in ICT Policies. Information Technologies & International Development, 13, 15.
  12. Andrews, D. W. & Lu, B. (2001). Consistent model and moment selection procedures for GMM estimation with application to dynamic panel data models. Journal of Econometrics, 101(1), 123-164. open in new tab
  13. Bagliano, F. C., & Morana, C. (2009). International macroeconomic dynamics: A factor vector autoregressive approach. Economic Modelling, 26(2), 432-444. open in new tab
  14. Bandiera, O., Buehren, N., Burgess, R., Goldstein, M., Gulesci, S., Rasul, I. & Sulaiman, M. (2017). Women"s empowerment in action: Evidence from a randomized control trial in Africa. World Bank. open in new tab
  15. Becketti, S. (2013). Introduction to time series using Stata (pp. 176-182). College Station, TX: Stata Press.
  16. Benería, L., Berik, G. & Floro, M. (2015). Gender, development and globalization: economics as if all people mattered. Routledge. open in new tab
  17. Bresnahan, T. F. & Trajtenberg, M. (1995). General purpose technologies "Engines of growth"?. Journal of econometrics, 65(1), 83-108. open in new tab
  18. Buvinic, M. & Furst-Nichols, R. (2014). Promoting women"s economic empowerment: what works? The World Bank. open in new tab
  19. Canova, F. & Ciccarelli, M. (2009). Estimating multicountry VAR models. International Economic Review, 50(3), 929-959. open in new tab
  20. Canova, F., & Ciccarelli, M. (2013). Panel Vector Autoregressive Models: A Survey☆ The views expressed in this article are those of the authors and do not necessarily reflect those of the ECB or the Eurosystem. In VAR Models in Macroeconomics-New Developments and Applications: Essays in Honor of Christopher A. Sims (pp. 205-246). Emerald Group Publishing Limited. open in new tab
  21. Castells, M., Fernandez-Ardevol, M., Qiu, J. L. & Sey, A. (2009). Mobile communication and society: A global perspective. MIT Press. open in new tab
  22. Clark, G. (2008). A farewell to alms: a brief economic history of the world. Princeton University Press.
  23. Cleveland, W. S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American statistical association, 74(368), 829-836. open in new tab
  24. Cornwall, A. (2016). Women"s empowerment: What works? Journal of International Development, 28(3), 342-359. open in new tab
  25. Dées, S. & Guntner, J. (2014). Analysing and forecasting price dynamics across euro area countries and sectors: A panel VAR approach. European Central Bank Working Paper Series, 1724. open in new tab
  26. Drucker, P. (2017). The age of discontinuity: Guidelines to our changing society. Routledge. open in new tab
  27. Fielden, S. L., Davidson, M. J., Gale, A. W. & Davey, C. L. (2000). Women in construction: the untapped resource. Construction Management & Economics, 18(1), 113-121. open in new tab
  28. Gaddis, I. & Klasen, S. (2014). Economic development, structural change, and women"s labor force participation. Journal of Population Economics, 27(3), 639-681. open in new tab
  29. Gnimassoun, B., & Mignon, V. (2016). How do macroeconomic imbalances interact? Evidence from a panel VAR analysis. Macroeconomic Dynamics, 20(7), 1717-1741. open in new tab
  30. Granger, C. W. (1980). Testing for causality: a personal viewpoint. Journal of Economic Dynamics and control, 2, 329-352. open in new tab
  31. Hafkin, N. J. & Huyer, S. (2006). Cinderella or cyberella?: Empowering women in the knowledge society. Kumarian Press, Incorporated.
  32. Hayakawa, K. (2016). Improved GMM estimation of panel VAR models. Computational Statistics & Data Analysis, 100, 240-264. open in new tab
  33. Hannan, E. J. & Quinn, B. G. (1979). The determination of the order of an autoregression. Journal of the Royal Statistical Society. Series B (Methodological), 41(2), 190-195. open in new tab
  34. Hansen, L. P. (1982). Large sample properties of generalized method of moments estimators. Econometrica: Journal of the Econometric Society, 50(4), 1029-1054. open in new tab
  35. Hanna, N. K., Guy, K. & Arnold, E. (1995). Information technology diffusion: Experience of industrial countries and lessons for developing countries. World Bank Staff Working Paper (1995). Washington DC The World Bank.
  36. Helpman, E. & Trajtenberg, M. (1996). Diffusion of general purpose technologies (No. w5773). National bureau of economic research. open in new tab
  37. ILO (2013). Guide to the Millennium Development Goals Employment Indicators. International Labour Office. open in new tab
  38. Islam, M. S. (2015). Impact of ICT on women empowerment in South Asia. Journal of Economic & Financial Studies, 3(03), 80-90. open in new tab
  39. ITU World Telecommunication/ICT Indicators database 2017. open in new tab
  40. Jovanovic, B. & Rousseau, P. L. (2005). General purpose technologies. Handbook of economic growth, 1, 1181-1224. open in new tab
  41. Kabeer, N. (2017). Economic pathways to women"s empowerment and active citizenship: what does the evidence from Bangladesh tell us? The Journal of Development Studies, 53(5), 649-663. open in new tab
  42. Kabir, N. (2016). Women"s economic empowerment and inclusive growth: labour markets and enterprise development. School of Oriental and African Studies, UK.
  43. Kaur, H., Lechman, E. & Marszk, A. (Eds.). (2017). Catalyzing development through ICT adoption: the developing world experience. Springer. open in new tab
  44. Klasen, S., Lechtenfeld, T. & Povel, F. (2015). A feminization of vulnerability? Female headship, poverty, and vulnerability in Thailand and Vietnam. World Development, 71, 36-53. open in new tab
  45. Klasen, S. (2018). What explains uneven female labor force participation levels and trends in developing countries? (No. 246). Courant Research Centre: Poverty, Equity and Growth-Discussion Papers. open in new tab
  46. Klasen, S. (2018a). The Impact of Gender Inequality on Economic Performance in Developing Countries. Annual Review of Resource Economics, 10, 279-298. open in new tab
  47. Koop, G. (2017). Bayesian methods for empirical macroeconomics with big data. Review of Economic Analysis, 9(1), 33-56. open in new tab
  48. Koop, G. & Korobilis, D. (2016). Model uncertainty in panel vector autoregressive models. European Economic Review, 81, 115-131. open in new tab
  49. Lechman, E. (2015). ICT Diffusion in Developing Countries. Springer International. Lindio-McGovern, L., & Wallimann, I. (2016). Globalization and third world women: Exploitation, coping and resistance. Routledge.
  50. Maddala, G. S. & Lahiri, K. (2009). Introduction to econometrics. Wiley. open in new tab
  51. McCullagh, P. & Nelder, J. A. (1989). Generalized Linear Models (Second Edition). Chapman and Hall/CRC. open in new tab
  52. Ng, S. & Perron, P. (2001). Lag length selection and the construction of unit root tests with good size and power. Econometrica: Journal of the Econometric Society, 69(6), 1519- 1554. open in new tab
  53. Ocampo, S. & Rodríguez, N. (2012). An introductory review of a structural VAR-X estimation and applications. Revista Colombiana de Estadística, 35(3), 479-508.
  54. Ortiz Rodríguez, J., & Pillai, V. K. (2019). Advancing support for gender equality among women in Mexico: Significance of labor force participation. International Social Work, 62(1), 172-184. open in new tab
  55. Perez, C. & Soete, L. (1988). Catching up in technology: entry barriers and windows of opportunity. Technical change and economic theory, 458-479.
  56. Pryer, J. A. (2017). Poverty and vulnerability in Dhaka slums: the urban livelihoods study. Routledge. open in new tab
  57. Ramey, V. A. & Shapiro, M. D. (1998). Costly capital reallocation and the effects of government spending. Carnegie-Rochester Conference Series on Public Policy, 48, 145-194. open in new tab
  58. Ranga, M. & Etzkowitz, H. (2010). Athena in the world of techne: The gender dimension of technology, innovation and entrepreneurship. Journal of technology management & innovation, 5(1), 1-12. open in new tab
  59. Sachs, C. E. (2018). Gendered fields: Rural women, agriculture, and environment. Routledge. open in new tab
  60. Shapiro, C., Carl, S., & Varian, H. R. (1998). Information rules: a strategic guide to the network economy. Harvard Business Press.
  61. Sigmund, M., Gunter, U., & Krenn, G. (2017). How Do Macroeconomic and Bank-specific Variables Influence Profitability in the Austrian Banking Sector? Evidence from a Panel Vector Autoregression Analysis. Economic Notes: Review of Banking, Finance and Monetary Economics, 46(3), 555-586. open in new tab
  62. Schwarz, G. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461- 464. open in new tab
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