تجزیه و تحلیل سری های زمانی در ارزیابی تاثیر فناوری اطلاعات و ارتباطات در سطح کل - درس و مفاهیم برای اقتصاد جدید
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|18012||2005||14 صفحه PDF||سفارش دهید|
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Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Information & Management, Volume 42, Issue 7, October 2005, Pages 1009–1022
The major role of information and communication technology (ICT) in the new economy is well documented: countries worldwide are pouring resources into their ICT infrastructure despite the widely acknowledged “productivity paradox”. Evaluating the contribution of ICT investments has become an elusive but important goal of IS researchers and economists. But this area of research is fraught with complexity and we have used Solow's Residual together with time-series analysis tools to overcome some methodological inadequacies of previous studies. Using this approach, we conduct a study of 20 countries to determine if there was empirical evidence to support claims that ICT investments are worthwhile. The results show that ICT contributes to economic growth in many developed countries and newly industrialized economies (NIEs), but not in developing countries. We finally suggest ICT-complementary factors, in an attempt to rectify possible flaws in ICT policies as a contribution towards improvement in global productivity.
The Nobel laureate economist Robert Solow once cited the infamous “productivity paradox” of the US economy, where productivity stagnated despite increasing computing power. His quip that “the computer age is everywhere but in the productivity statistics”  might apply to other advanced economies as well. Much of the early research of the 1970s and 1980s also indicated the negative effects of computers on productivity , , , ,  and . A number of authors attempted to provide justifications for the post-1970s “clash of expectations and statistics”. Their review of the paradox  and  produced a gamut of explanations, including mismeasurement of outputs and inputs and lags due to learning and adjustment. The most widely recognized explanation for the post-1973 productivity slowdown was flaws in methodological frameworks and measurement errors. Another explanation was that the main benefits from using computers – improved quality, timeliness, and customization  – were not properly measured in official productivity statistics. In the 1990s, a number of researchers sought to find a positive contribution of information and communication technology (ICT) to economic growth. Brynjolfsson and Yang  cited contemporary studies that had associated ICT with productivity growth. While refuting the productivity paradox, authors of recent studies have attributed this change to improved data quality and a new econometric framework that produced more satisfying empirical results. At the firm and industry level, several authors have noted positive evidence of returns from ICT investments ,  and . Their results have been confirmed by a number of recent studies and initiated a large stream of research. However, there are limitations to the implications of the results. In particular, as the ICT productivity paradox was originally defined at the economy level, one natural concern was that most of these recent IS studies have addressed the productivity question at the micro level  and . In contrast to investigations at the firm and industry levels, studies at the aggregate level have not been conclusive. They have also suffered from limitations in their analysis. For instance, in their country-level research in the Asia Pacific area, Kraemer and Dedrick  found that a positive correlation existed between ICT and economic growth. However, they acknowledged that they could not provide conclusive evidence of a causal relationship, given the relatively small portion of the economy allocated to ICT in the overall capital and the broad array of factors affecting economic growth. Similarly, Jorgenson and Stiroh  discovered that computer capital contributed to growth more than ordinary capital, suggesting a positive payoff from ICT. However, the extrapolation of total factor productivity (TFP) growth for long-term projections is questionable. Even the researchers themselves admitted: “Only as the statistical agencies continue their slow progress towards improved data and implementation of state-of-the-art methodology will this murky picture become more transparent.” Pohjola  indicated that disappointment in ICT is still chronicled in many macroeconomic studies, because the impact on productivity and economic growth has been much harder to detect. Therefore, better measurement methods and definitions are required for more precise appraisal, especially in the Internet and e-commerce era. In response, we proposed the use of Solow's Residual together with time-series analysis tools to overcome the methodology inadequacies of previous studies. Our goal was to establish empirical evidences to assess previous productivity strategies. Our hope was that our findings would help guide future ICT investment decisions in both developing and developed countries. The use of Solow's Residual offers the ability of better measuring the productivity attributable to technology. The majority of earlier research used tangible outputs, such as gross domestic product (GDP), national wealth, and revenue; these output measures might not capture the full contribution of ICT to an economy's productivity, because the impact of ICT usage is generally considered to be wide-ranging but intangible. Solow's Residual, which provides more information about changes in technology than other productivity measures, should therefore better appraise the effectiveness of the use of ICT. For each of the countries sampled here, we first investigated the causal relationship between ICT and GDP by looking directly at the production function. Then we derived Solow's Residual for the country in order to analyze the impact of ICT on its economic growth. In both analyses, we incorporated time series statistical tools because all the variables – GDP, capital, labor and ICT – were generally generated for a particular instance in time. Econometricians, in their investigations, have often imposed theories on data even when its temporal structure does not conform to their theories; this inadequacy is common in studies on the relationship between ICT and productivity. In our study, we implemented time series analysis tools to eliminate this spurious regression problem. Because time series tools allow the researcher to test data stationarity before making any further analyses, corrective measures can be incorporated in the statistical tests; the researcher would thus be spared the potential problems of ordinary regression. Thus, more consistent empirical findings can be expected from our methodology. Traditional regression methods are susceptible to the limitation of reliable forecasting; similarly, the predicted values of the variable would also have to be near the range of the sample values . In contrast, time series tools allow the contribution of ICT capital to be more accurately projected into the future. This is absolutely important, because the value of ICT does not present itself at any particular point in time but rather unfolds as ICT applications and infrastructure are put into effective use. Moreover, finding a strong association between ICT investment and growth does not necessarily imply a causal relationship. If non-stationary time series variables are not cointegrated, then a high degree of correlation between two variables does not mean a causal relationship between them. The time series methodology thus allows us to recognize and avoid spurious results. Obviously, time does not go backwards. Using a time series methodology, we can use lags to identify causal relationships. This is not possible in cross-sectional studies. The time series methodology also allows us to answer some specific questions. For example, we can find out whether the relationship between variables is long- or short-run. The Granger causality test enables us to determine the direction of causality and find out whether ICT growth causes GDP growth, whether GDP growth causes ICT growth, or whether there is a feedback effect between ICT and GDP. Longitudinal or panel data analyses, although rather resource intensive, allow researchers to obtain a deeper understanding of the impact of technologies along the continuum of ICT investment . As Kohli and Devaraj  suggested, researchers should gather larger samples including longitudinal or panel data to assess the effects of ICT payoff. Such data can often improve the accuracy of the results, because they can control for country (industry or firm) specific effects. Application of this data also allows the researcher to examine the lag effects of technological impact  and . This is an advantage, as neglect of lag effects has been cited as a factor contributing to the productivity paradox  and . Economic analyses of growth operate on the belief that it is in some way related to qualitative change. The assumption is that growth is not just the extension of an existing activity but involves doing new things with new processes, which entail a change in the character of the activity. For instance, Adam Smith  perceived that growth was associated with a more complex division of labor: the components of existing activities would spin off as separate activities and be subject to productivity growth as people specialized in them and became more skilful at carrying them out. Smith also predicted that knowledge creation would become a separate activity and that this would further drive productivity growth . Cross-country studies on the productivity impact of ICT are still relatively scarce, primarily because comparable data sources are quite new. Despite the fact that the productivity paradox of ICT has been considered to be an international phenomenon, Dewan and Kraemer  noted, most of the existing studies involve firm-level analysis , , ,  and  conducted mainly in the US. Mahmood and Mann  asserted that it was important for researchers to include an international dimension to ICT investment-performance relationships and extend their research focus beyond the US to encompass the experience of other countries. Hence, we sought to make a significant contribution to the value of ICT investment by using new findings on international experiences with ICT investment. The answers to our research questions should have important theoretical and practical implications. By making comparisons among countries to appraise the cause of growth disparities, we attempted to identify the characteristics of national innovation systems that were linked to strong innovative performance. More importantly, we intended to uncover evidence to support the view that the contribution of ICT can be a long-term, sustainable phenomenon. For practitioners, the empirical findings should then serve to shed light on ICT policy making.
نتیجه گیری انگلیسی
ICT and productivity have been considered by many scholars. However, our study is among the first to approach the topic employing Solow's Residual instead of tangible outputs and time series analysis tools at the country level. Consistent with previous findings , we discovered that ICT investments have been contributing to improvement in the national productivity of several developed countries and newly industrialized economies (NIEs), but not of developing nations. To allow for the limitations in the data sets, the material was obtained from the “best” available – even if only one set of ICT data series provided positive evidence of the relationship, the results from the other ICT data series were discarded. Even though there is no agreement on the minimum number of periods required in time series statistics tests, scholars have tacitly agreed that cointegration testing on small samples still leaves something to be desired . Thus the data period analyzed here may be insufficient to capture long-term effects. In addition, inferences from the Granger causality tests may be unfair for the relatively small sample set of annual values for A and ICT, which could ignore short-run effects. The values of the ICT variable are problematic also: there are no sources that provide these values over a period of more than 10 years. Consequently, telecommunications investments had to be used as a proxy, even though they could prove inadequate in reflecting the full effect of ICT in some countries’ productivity. Nonetheless, we believe that the study has contributed to development literature and provided useful groundwork for time series analyses in ICT and productivity research. In recent years, studies have recommended ICT production-close-to-use, which promotes the interaction between ICT producers and users, and facilitates the development of software and information services. According to Kraemer and Dedrick , policies could include: the promotion of small business ICT use, provision of financial support to ICT companies, and encouragement of partnerships between local firms and multinationals. Indeed, countrywide diffusion of technology could deliver increasing returns to investments and competitiveness, given today's global markets and pervasiveness of the Internet and e-commerce. From the consistency between our findings and previous studies, countries may need to put in place ICT-complementary factors in tandem with their ICT investments. The proven existence of a long-term relationship between ICT and growth in several countries would encourage belief that the phenomenon is sustainable, and that nations can rely on ICT investments to attain economic expansion, rather than resort to an increase in the traditional production inputs of human labor and capital.