جستجوی مقالات مرتبط با کلیدواژه « provincial data » در نشریات گروه « اقتصاد »

In recent decades, increasing role of productivity contribution in economic growth has been highly emphasized, especially in developing countries such as Iran which are facing low rate of productivity and resource scarcity. In this context one of the main influencing factors on productivity and efficiency is information and communication technology (ICT) known virtual space. Global experiences imply that virtual space could be able to stimulate job creation and value added creation. This is the main theme of this paper.

We apply parametric (Panel Data) & non-parametric (DEA) approach through provincial data. We manage it to understand not only the average effect of virtual space on national product (known as productivity) but the relative position of each province in terms of virtual space contribution in national product, in favor of efficiency.

The findings imply that virtual space, as a production input, could stimulate national product positively, although its impact has been much smaller that other production input (Capital & Labor force). Meanwhile it had significant impact on relative production efficiency in provincial level as well. However by ignoring virtual space in our basic model, the provinces efficiencies decrease by 8.6%. These results shed light on stimulating effect of virtual space on national product.

Increasing cyber space penetration rate, reducing the ICT gap between the provinces, coincided by decreasing access cost of economic agents can be considered as proper policy recommendations.

Investment and capital stock variables are considered as critical data requirements in economic policy making. In this context, having access to the statistics and performance of these variables is regarded as one of the requirements in economic planning. It will be more important especially at levels beyond the national level such as provincial level at which the data are not produced by national institutions responsible for economic statistics. In order to meet this need, in this paper we have tried to calculate the provincial capital stock index and its alternative variables using the capital stock estimation methods. To do that, an approach is introduced and applied to estimate the capital stock variable at provincial level by reviewing the literature of production function,. Also two alternative variables and their related data are suggested for a sample period 2006-2012. The results could be applicable not only in comparative studies and policy making at provincial and regional levels but in quantitative studies in the field of productivity and efficiency, economic growth ,saving and investment and input – output analysis.</span>