871 resultados para Panel data probit model


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In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular it delivers a zero-limiting mean-squared error if the number of forecasts and the number of post-sample time periods is sufficiently large. We also develop a zero-mean test for the average bias. Monte-Carlo simulations are conducted to evaluate the performance of this new technique in finite samples. An empirical exercise, based upon data from well known surveys is also presented. Overall, these results show promise for the bias-corrected average forecast.

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In this paper, we propose a novel approach to econometric forecasting of stationary and ergodic time series within a panel-data framework. Our key element is to employ the (feasible) bias-corrected average forecast. Using panel-data sequential asymptotics we show that it is potentially superior to other techniques in several contexts. In particular, it is asymptotically equivalent to the conditional expectation, i.e., has an optimal limiting mean-squared error. We also develop a zeromean test for the average bias and discuss the forecast-combination puzzle in small and large samples. Monte-Carlo simulations are conducted to evaluate the performance of the feasible bias-corrected average forecast in finite samples. An empirical exercise, based upon data from a well known survey is also presented. Overall, these results show promise for the feasible bias-corrected average forecast.

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Este Artigo Testa a Proposição da Teoria Econômica de que Propriedade Intelectual e Defesa da Concorrência são Políticas Complementares. um Modelo Probit Ordenado é Utilizado para Estimar os Efeitos Marginais do Uso e Qualidade do Enforcement dos Direitos de Propriedade Intelectual em uma Medida da Gravidade dos Problemas Relacionados À Concorrência. os Resultados Obtidos Reforçam a Noção de que as Políticas de Concorrência e Propriedade Intelectual não são Contraditórias.

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Using the Pricing Equation in a panel-data framework, we construct a novel consistent estimator of the stochastic discount factor (SDF) which relies on the fact that its logarithm is the "common feature" in every asset return of the economy. Our estimator is a simple function of asset returns and does not depend on any parametric function representing preferences. The techniques discussed in this paper were applied to two relevant issues in macroeconomics and finance: the first asks what type of parametric preference-representation could be validated by asset-return data, and the second asks whether or not our SDF estimator can price returns in an out-of-sample forecasting exercise. In formal testing, we cannot reject standard preference specifications used in the macro/finance literature. Estimates of the relative risk-aversion coefficient are between 1 and 2, and statistically equal to unity. We also show that our SDF proxy can price reasonably well the returns of stocks with a higher capitalization level, whereas it shows some difficulty in pricing stocks with a lower level of capitalization.

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Using the theoretical framework of Lettau and Ludvigson (2001), we perform an empirical investigation on how widespread is the predictability of cay {a modi ed consumption-wealth ratio { once we consider a set of important countries from a global perspective. We chose to work with the set of G7 countries, which represent more than 64% of net global wealth and 46% of global GDP at market exchange rates. We evaluate the forecasting performance of cay using a panel-data approach, since applying cointegration and other time-series techniques is now standard practice in the panel-data literature. Hence, we generalize Lettau and Ludvigson's tests for a panel of important countries. We employ macroeconomic and nancial quarterly data for the group of G7 countries, forming an unbalanced panel. For most countries, data is available from the early 1990s until 2014Q1, but for the U.S. economy it is available from 1981Q1 through 2014Q1. Results of an exhaustive empirical investigation are overwhelmingly in favor of the predictive power of cay in forecasting future stock returns and excess returns.

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Includes bibliography

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The atmosphere is a global influence on the movement of heat and humidity between the continents, and thus significantly affects climate variability. Information about atmospheric circulation are of major importance for the understanding of different climatic conditions. Dust deposits from maar lakes and dry maars from the Eifel Volcanic Field (Germany) are therefore used as proxy data for the reconstruction of past aeolian dynamics.rnrnIn this thesis past two sediment cores from the Eifel region are examined: the core SM3 from Lake Schalkenmehren and the core DE3 from the Dehner dry maar. Both cores contain the tephra of the Laacher See eruption, which is dated to 12,900 before present. Taken together the cores cover the last 60,000 years: SM3 the Holocene and DE3 the marine isotope stages MIS-3 and MIS-2, respectively. The frequencies of glacial dust storm events and their paleo wind direction are detected by high resolution grain size and provenance analysis of the lake sediments. Therefore two different methods are applied: geochemical measurements of the sediment using µXRF-scanning and the particle analysis method RADIUS (rapid particle analysis of digital images by ultra-high-resolution scanning of thin sections).rnIt is shown that single dust layers in the lake sediment are characterized by an increased content of aeolian transported carbonate particles. The limestone-bearing Eifel-North-South zone is the most likely source for the carbonate rich aeolian dust in the lake sediments of the Dehner dry maar. The dry maar is located on the western side of the Eifel-North-South zone. Thus, carbonate rich aeolian sediment is most likely to be transported towards the Dehner dry maar within easterly winds. A methodology is developed which limits the detection to the aeolian transported carbonate particles in the sediment, the RADIUS-carbonate module.rnrnIn summary, during the marine isotope stage MIS-3 the storm frequency and the east wind frequency are both increased in comparison to MIS-2. These results leads to the suggestion that atmospheric circulation was affected by more turbulent conditions during MIS-3 in comparison to the more stable atmospheric circulation during the full glacial conditions of MIS-2.rnThe results of the investigations of the dust records are finally evaluated in relation a study of atmospheric general circulation models for a comprehensive interpretation. Here, AGCM experiments (ECHAM3 and ECHAM4) with different prescribed SST patterns are used to develop a synoptic interpretation of long-persisting east wind conditions and of east wind storm events, which are suggested to lead to an enhanced accumulation of sediment being transported by easterly winds to the proxy site of the Dehner dry maar.rnrnThe basic observations made on the proxy record are also illustrated in the 10 m-wind vectors in the different model experiments under glacial conditions with different prescribed sea surface temperature patterns. Furthermore, the analysis of long-persisting east wind conditions in the AGCM data shows a stronger seasonality under glacial conditions: all the different experiments are characterized by an increase of the relative importance of the LEWIC during spring and summer. The different glacial experiments consistently show a shift from a long-lasting high over the Baltic Sea towards the NW, directly above the Scandinavian Ice Sheet, together with contemporary enhanced westerly circulation over the North Atlantic.rnrnThis thesis is a comprehensive analysis of atmospheric circulation patterns during the last glacial period. It has been possible to reconstruct important elements of the glacial paleo climate in Central Europe. While the proxy data from sediment cores lead to a binary signal of the wind direction changes (east versus west wind), a synoptic interpretation using atmospheric circulation models is successful. This shows a possible distribution of high and low pressure areas and thus the direction and strength of wind fields which have the capacity to transport dust. In conclusion, the combination of numerical models, to enhance understanding of processes in the climate system, with proxy data from the environmental record is the key to a comprehensive approach to paleo climatic reconstruction.rn

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Radiocarbon production, solar activity, total solar irradiance (TSI) and solar-induced climate change are reconstructed for the Holocene (10 to 0 kyr BP), and TSI is predicted for the next centuries. The IntCal09/SHCal04 radiocarbon and ice core CO2 records, reconstructions of the geomagnetic dipole, and instrumental data of solar activity are applied in the Bern3D-LPJ, a fully featured Earth system model of intermediate complexity including a 3-D dynamic ocean, ocean sediments, and a dynamic vegetation model, and in formulations linking radiocarbon production, the solar modulation potential, and TSI. Uncertainties are assessed using Monte Carlo simulations and bounding scenarios. Transient climate simulations span the past 21 thousand years, thereby considering the time lags and uncertainties associated with the last glacial termination. Our carbon-cycle-based modern estimate of radiocarbon production of 1.7 atoms cm−2 s−1 is lower than previously reported for the cosmogenic nuclide production model by Masarik and Beer (2009) and is more in-line with Kovaltsov et al. (2012). In contrast to earlier studies, periods of high solar activity were quite common not only in recent millennia, but throughout the Holocene. Notable deviations compared to earlier reconstructions are also found on decadal to centennial timescales. We show that earlier Holocene reconstructions, not accounting for the interhemispheric gradients in radiocarbon, are biased low. Solar activity is during 28% of the time higher than the modern average (650 MeV), but the absolute values remain weakly constrained due to uncertainties in the normalisation of the solar modulation to instrumental data. A recently published solar activity–TSI relationship yields small changes in Holocene TSI of the order of 1 W m−2 with a Maunder Minimum irradiance reduction of 0.85 ± 0.16 W m−2. Related solar-induced variations in global mean surface air temperature are simulated to be within 0.1 K. Autoregressive modelling suggests a declining trend of solar activity in the 21st century towards average Holocene conditions.

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A main assumption of social production function theory is that status is a major determinant of subjective well-being (SWB). From the perspective of the dissociative hypothesis, however, upward social mobility may be linked to identity problems, distress, and reduced levels of SWB because upwardly mobile people lose their ties to their class of origin. In this paper, we examine whether or not one of these arguments holds. We employ the United Kingdom and Switzerland as case studies because both are linked to distinct notions regarding social inequality and upward mobility. Longitudinal multilevel analyses based on panel data (UK: BHPS, Switzerland: SHP) allow us to reconstruct individual trajectories of life satisfaction (as a cognitive component of SWB) along with events of intragenerational and intergenerational upward mobility—taking into account previous levels of life satisfaction, dynamic class membership, and well-studied determinants of SWB. Our results show some evidence for effects of social class and social mobility on well-being in the UK sample, while there are no such effects in the Swiss sample. The UK findings support the idea of dissociative effects in terms of a negative effect of intergenerational upward mobility on SWB.

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The evolution of the northwest African hydrological balance throughout the Pleistocene epoch influenced the migration of prehistoric humans**1. The hydrological balance is also thought to be important to global teleconnection mechanisms during Dansgaard-Oeschger and Heinrich events**2. However, most high-resolution African climate records do not span the millennial-scale climate changes of the last glacial-interglacial cycle**1, 3, 4, 5, or lack an accurate chronology**6. Here, we use grain-size analyses of siliciclastic marine sediments from off the coast of Mauritania to reconstruct changes in northwest African humidity over the past 120,000 years. We compare this reconstruction to simulations of palaeo-humidity from a coupled atmosphere-ocean-vegetation model. These records are in good agreement, and indicate the reoccurrence of precession-forced humid periods during the last interglacial period similar to the Holocene African Humid Period. We suggest that millennial-scale arid events are associated with a reduction of the North Atlantic meridional overturning circulation and that millennial-scale humid events are linked to a regional increase of winter rainfall over the coastal regions of northwest Africa.

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In September 1999, the International Monetary Fund (IMF) established the Poverty Reduction and Growth Facility (PRGF) to make the reduction of poverty and the enhancement of economic growth the fundamental objectives of lending operations in its poorest member countries. This paper studies the spending and absorption of aid in PRGF-supported programs, verifies whether the use of aid is programmed to be smoothed over time, and analyzes how considerations about macroeconomic stability influence the programmed use of aid. The paper shows that PRGF-supported programs permit countries to utilize all increases in aid within a few years, showing smoothed use of aid inflows over time. Our results reveal that spending is higher than absorption in both the long-run and short-run use of aid, which is a robust finding of the study. Furthermore, the paper demonstrates that the long-run spending exceeds the injected increase of aid inflows in the economy. In addition, the paper finds that the presence of a PRGF-supported program does not influence the actual absorption or spending of aid.

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This paper examines empirically whether financial deepening has contributed to poverty reduction in India. Using unbalanced panel data for 28 states and union territories between 1973 and 2004, we estimate models in which the poverty ratio is explained by financial deepening, controlling for international openness, inflation rate, and economic growth. From the dynamic generalised method of moments (GMM) estimation, we find that financial deepening and economic growth alleviate poverty, while international openness and the inflation rate have the opposite effect. These results are robust to changes in the poverty ratios in rural areas, urban areas, and the whole economy.

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The paper focuses on the recent pattern of government consumption expenditure in developing countries and estimates the determinants which have influenced government expenditure. Using a panel data set for 111 developing countries from 1984 to 2004, this study finds evidence that political and institutional variables as well as governance variables significantly influence government expenditure. Among other results, the paper finds new evidence of Wagner's law which states that peoples' demand for service and willingness to pay is income-elastic hence the expansion of public economy is influenced by the greater economic affluence of a nation (Cameron1978). Corruption is found to be influential in explaining the public expenditure of developing countries. On the contrary, size of the economy and fractionalization are found to have significant negative association with government expenditure. In addition, the study finds evidence that public expenditure significantly shrinks under military dictatorship compared with other form of governance.

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Improving the knowledge of demand evolution over time is a key aspect in the evaluation of transport policies and in forecasting future investment needs. It becomes even more critical for the case of toll roads, which in recent decades has become an increasingly common device to fund road projects. However, literature regarding demand elasticity estimates in toll roads is sparse and leaves some important aspects to be analyzed in greater detail. In particular, previous research on traffic analysis does not often disaggregate heavy vehicle demand from the total volume, so that the specific behavioral patternsof this traffic segment are not taken into account. Furthermore, GDP is the main socioeconomic variable most commonly chosen to explain road freight traffic growth over time. This paper seeks to determine the variables that better explain the evolution of heavy vehicle demand in toll roads over time. To that end, we present a dynamic panel data methodology aimed at identifying the key socioeconomic variables that explain the behavior of road freight traffic throughout the years. The results show that, despite the usual practice, GDP may not constitute a suitable explanatory variable for heavy vehicle demand. Rather, considering only the GDP of those sectors with a high impact on transport demand, such as construction or industry, leads to more consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period. This is an interesting case in the international context, as road freight demand has experienced an even greater reduction in Spain than elsewhere, since the beginning of the economic crisis in 2008.

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Tolls have increasingly become a common mechanism to fund road projects in recent decades. Therefore, improving knowledge of demand behavior constitutes a key aspect for stakeholders dealing with the management of toll roads. However, the literature concerning demand elasticity estimates for interurban toll roads is still limited due to their relatively scarce number in the international context. Furthermore, existing research has left some aspects to be investigated, among others, the choice of GDP as the most common socioeconomic variable to explain traffic growth over time. This paper intends to determine the variables that better explain the evolution of light vehicle demand in toll roads throughout the years. To that end, we establish a dynamic panel data methodology aimed at identifying the key socioeconomic variables explaining changes in light vehicle demand over time. The results show that, despite some usefulness, GDP does not constitute the most appropriate explanatory variable, while other parameters such as employment or GDP per capita lead to more stable and consistent results. The methodology is applied to Spanish toll roads for the 1990?2011 period, which constitutes a very interesting case on variations in toll road use, as road demand has experienced a significant decrease since the beginning of the economic crisis in 2008.