116 resultados para GDP Interpolation


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The rise in world trade since 1970 has been accompanied by a rise in the geographic span of control of management and, hence, also a rise in the e ective international mobility of labor services. We study the e ect of such a globalization of the world's labor markets. The world's welfare gains depend positively on the skill-heterogeneity of the world's labor force. We nd that when peoplecan choose between wage work and managerial work, the worldwide labor market raises output by more in the rich and the poor countries, and by less in the middle-income countries. This is because the middle-income countries experience the smallest change in the factor-price ratio, and where the option to choose between wage work and managerial work has the least value in the integratedeconomy. Our theory also establishes that after economic integration, the high skill countries see a disproportionate increase in managerial occupations. Using aggregate data on GDP, openness and occupations from 115 countries, we find evidence for these patterns of occupational choice.

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Demosaicking is a particular case of interpolation problems where, from a scalar image in which each pixel has either the red, the green or the blue component, we want to interpolate the full-color image. State-of-the-art demosaicking algorithms perform interpolation along edges, but these edges are estimated locally. We propose a level-set-based geometric method to estimate image edges, inspired by the image in-painting literature. This method has a time complexity of O(S) , where S is the number of pixels in the image, and compares favorably with the state-of-the-art algorithms both visually and in most relevant image quality measures.

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In this work we propose a new automatic methodology for computing accurate digital elevation models (DEMs) in urban environments from low baseline stereo pairs that shall be available in the future from a new kind of earth observation satellite. This setting makes both views of the scene similarly, thus avoiding occlusions and illumination changes, which are the main disadvantages of the commonly accepted large-baseline configuration. There still remain two crucial technological challenges: (i) precisely estimating DEMs with strong discontinuities and (ii) providing a statistically proven result, automatically. The first one is solved here by a piecewise affine representation that is well adapted to man-made landscapes, whereas the application of computational Gestalt theory introduces reliability and automation. In fact this theory allows us to reduce the number of parameters to be adjusted, and tocontrol the number of false detections. This leads to the selection of a suitable segmentation into affine regions (whenever possible) by a novel and completely automatic perceptual grouping method. It also allows us to discriminate e.g. vegetation-dominated regions, where such an affine model does not apply anda more classical correlation technique should be preferred. In addition we propose here an extension of the classical ”quantized” Gestalt theory to continuous measurements, thus combining its reliability with the precision of variational robust estimation and fine interpolation methods that are necessary in the low baseline case. Such an extension is very general and will be useful for many other applications as well.

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This paper discusses the role of deterministic components in the DGP and in the auxiliary regression model which underlies the implementation of the Fractional Dickey-Fuller (FDF) test for I(1) against I(d) processes with d ∈ [0, 1). This is an important test in many economic applications because I(d) processess with d & 1 are mean-reverting although, when 0.5 ≤ d & 1,, like I(1) processes, they are nonstationary. We show how simple is the implementation of the FDF in these situations, and argue that it has better properties than LM tests. A simple testing strategy entailing only asymptotically normally distributed tests is also proposed. Finally, an empirical application is provided where the FDF test allowing for deterministic components is used to test for long-memory in the per capita GDP of several OECD countries, an issue that has important consequences to discriminate between growth theories, and on which there is some controversy.

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This paper proposes a method to conduct inference in panel VAR models with cross unit interdependencies and time variations in the coefficients. The approach can be used to obtain multi-unit forecasts and leading indicators and to conduct policy analysis in a multiunit setups. The framework of analysis is Bayesian and MCMC methods are used to estimate the posterior distribution of the features of interest. The model is reparametrized to resemble an observable index model and specification searches are discussed. As an example, we construct leading indicators for inflation and GDP growth in the Euro area using G-7 information.

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The aim of this paper is to test formally the classical business cycle hypothesis, using data from industrialized countries for the time period since 1960. The hypothesis is characterized by the view that the cyclical structure in GDP is concentrated in the investment series: fixed investment has typically a long cycle, while the cycle in inventory investment is shorter. To check the robustness of our results, we subject the data for 15 OECD countries to a variety of detrending techniques. While the hypothesis is not confirmed uniformly for all countries, there is a considerably high number for which the data display the predicted pattern. None of the countries shows a pattern which can be interpreted as a clear rejection of the classical hypothesis.

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We find that trade and domestic market size are robust determinants of economic growth over the 1960-1996 period when trade openness is measured as the US dollar value of imports and exports relative to GDP in PPP US$ ('real openness'). When trade openness is measured as the US dollar value of imports and exports relative to GDP in exchange rate US$ ('nominal openness') however, trade and the size of domestic markets are often non-robust determinants of growth. We argue that real openness is the more appropriate measure of trade and that our empirical results should be seen as evidence in favor of the extent-of-the-market hypothesis.

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The view of a 1870-1913 expanding European economy providing increasing welfare to everybody has been challenged by many, then and now. We focus on the amazing growth that was experienced, its diffusion and its sources, in the context of the permanent competition among European nation states. During 1870-193 the globalized European economy reached a silver age . GDP growth was quite rapid (2.15% per annum) and diffused all over Europe. Even discounting the high rates of population growth (1.06%), per capita growth was left at a respectable 1.08%. Income per capita was rising in every country, and the rates of improvement were quite similar. This was a major achievement after two generations of highly localized growth, both geographically and socially. Growth was based on the increased use of labour and capital, but a good part of growth (73 per cent for the weighted average of the best documented European countries) came out of total factor productivity efficiency gains resulting from not well specified ultimate sources of growth. This proportion suggests that the European economy was growing at full capacity at its production frontier. It would have been very difficult to improve its performance. Within Europe, convergence was limited, and it only was in motion after 1900. What happened was more the end of the era of big divergence rather than an era of convergence.

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An analysis of the performance of GDP, employment and otherlabor market variables following the troughs in postwar U.S. businesscycles points to much slower recoveries in the three most recentepisodes, but does not reveal any significant change over time in therelation between GDP and employment. This leads us to characterizethe last three episodes as slow recoveries, as opposed to jobless recoveries.We use the estimated New Keynesian model in Galí-Smets-Wouters (2011) to provide a structural interpretation for the slowerrecoveries since the early nineties.

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The present paper revisits an old theme in Latin American and Chilean economic history; the early industrialization in the XIX - XX centuries. The difference with previous approaches is the elaboration of new quantitative series of Chilean machinery investment in the long run and its relative prices and composition, in the period when some authors have sited the beginning of the industrialization in the continent. Initial findings, based on the participation of capital formation in machinery imports and GDP, do not reinforce the idea of early industrialization in Chile.

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We show that the welfare of a representative consumer can be related to observable aggregatedata. To a first order, the change in welfare is summarized by (the present value of) the Solowproductivity residual and by the growth rate of the capital stock per capita. We also show thatproductivity and the capital stock suffice to calculate differences in welfare across countries, withboth variables computed as log level deviations from a reference country. These results hold forarbitrary production technology, regardless of the degree of product market competition, and applyto open economies as well if TFP is constructed using absorption rather than GDP as the measureof output. They require that TFP be constructed using prices and quantities as perceived byconsumers. Thus, factor shares need to be calculated using after-tax wages and rental rates, andwill typically sum to less than one. We apply these results to calculate welfare gaps and growthrates in a sample of developed countries for which high-quality TFP and capital data are available.We find that under realistic scenarios the United Kingdom and Spain had the highest growth ratesof welfare over our sample period of 1985-2005, but the United States had the highest level ofwelfare.

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We investigate the determinants of regional development using a newly constructed database of 1569 sub-national regions from 110 countries covering 74 percent of the world s surface and 97 percent of its GDP. We combine the cross-regional analysis of geographic, institutional, cultural, and human capital determinants of regional development with an examination of productivity in several thousand establishments located in these regions. To organize the discussion, we present a new model of regional development that introduces into a standard migration framework elements of both the Lucas (1978) model of the allocation of talent between entrepreneurship and work, and the Lucas (1988) model of human capital externalities. The evidence points to the paramount importance of human capital in accounting for regional differences in development, but also suggests from model estimation and calibration that entrepreneurial inputs and possibly human capital externalities help understand the data.

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We examine the effect of oil price fluctuations ondemocratic institutions over the 1960-2007 period. We also exploitthe very persistent response of income to oil price fluctuations tostudy the effect of persistent (oil price-driven) income shocks ondemocracy. Our results indicate that countries with greater net oilexports over GDP see improvements in democratic institutionsfollowing upturns in international oil prices. We estimate that a 1percentage point increase in per capita GDP growth due to apositive oil price shock increases the Polity democracy score byaround 0.2 percentage points on impact and by around 2 percentagepoints in the long run. The effect on the probability of a democratictransition is around 0.4 percentage points.

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This paper discusses the role of deterministic components in the DGP and in the auxiliaryregression model which underlies the implementation of the Fractional Dickey-Fuller (FDF) test for I(1) against I(d) processes with d [0, 1). This is an important test in many economic applications because I(d) processess with d < 1 are mean-reverting although, when 0.5 = d < 1, like I(1) processes, they are nonstationary. We show how simple is the implementation of the FDF in these situations, and argue that it has better properties than LM tests. A simple testing strategy entailing only asymptotically normally distributedtests is also proposed. Finally, an empirical application is provided where the FDF test allowing for deterministic components is used to test for long-memory in the per capita GDP of several OECD countries, an issue that has important consequences to discriminate between growth theories, and on which there is some controversy.

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We address the question of whether growth and welfare can be higher in crisis prone economies. First, we show that there is a robust empirical link between per-capita GDP growth and negative skewness of credit growth across countries with active financial markets. That is, countries that have experienced occasional crises have grown on average faster than countries with smooth credit conditions. We then present a two-sector endogenous growth model in which financial crises can occur, and analyze the relationship between financial fragility and growth. The underlying credit market imperfections generateborrowing constraints, bottlenecks and low growth. We show that under certain conditions endogenous real exchange rate risk arises and firms find it optimal to take on credit risk in the form of currency mismatch. Along such a risky path average growth is higher, but self-fulfilling crises occur occasionally. Furthermore, we establish conditions under which the adoption of credit risk is welfare improving and brings the allocation nearer to the Pareto optimal level. The design of the model is motivated by several features of recent crises: credit risk in the form of foreign currency denominated debt; costly crises that generate firesales and widespread bankruptcies; and asymmetric sectorial responses, wherethe nontradables sector falls more than the tradables sector in the wake of crises.