43 resultados para Fama-MacBeth regressions
Resumo:
The relationship between income and nutrient intake is explored. Nonparametric, panel, and quantile regressions are used. Engle curves for calories, fat, and protein are approximately linear in logs with carbohydrate intakes exhibiting diminishing elasticities as incomes increase. Elasticities range from 0.10 to 0.25, with fat having the highest elasticities. Countries in higher quantiles have lower elasticities than those in lower quantiles. Results predict significant cumulative increases in calorie consumption which are increasingly composed of fats. Though policies aimed at poverty alleviation and economic growth may assuage hunger and malnutrition, they may also exacerbate problems associated with obesity.
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Drawing upon an updated and expanded dataset of Energy Star and LEED labeled commercial offices, this paper investigates the effect of eco-labeling on rental rates, sale prices and occupancy rates. Using OLS and robust regression procedures, hedonic modeling is used to test whether the presence of an eco-label has a significant positive effect on rental rates, sale prices and occupancy rates. The study suggests that estimated coefficients can be sensitive to outlier treatment. For sale prices and occupancy rates, there are notable differences between estimated coefficients for OLS and robust regressions. The results suggest that both Energy Star and LEED offices obtain rental premiums of approximately 3%. A 17% sale price premium is estimated for Energy Star labeled offices but no significant sale price premium is estimated for LEED labeled offices. Surprisingly, no significant occupancy premium is estimated for Energy Star labeled offices and a negative occupancy premium is estimated for LEED labeled offices.
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Environmental cues influence the development of stomata on the leaf epidermis, and allow plants to exert plasticity in leaf stomatal abundance in response to the prevailing growing conditions. It is reported that Arabidopsis thaliana ‘Landsberg erecta’ plants grown under low relative humidity have a reduced stomatal index and that two genes in the stomatal development pathway, SPEECHLESS and FAMA, become de novo cytosine methylated and transcriptionally repressed. These environmentally-induced epigenetic responses were abolished in mutants lacking the capacity for de novo DNA methylation, for the maintenance of CG methylation, and in mutants for the production of short-interfering non-coding RNAs (siRNAs) in the RNA-directed DNA methylation pathway. Induction of methylation was quantitatively related to the induction of local siRNAs under low relative humidity. Our results indicate the involvement of both transcriptional and post-transcriptional gene suppression at these loci in response to environmental stress. Thus, in a physiologically important pathway, a targeted epigenetic response to a specific environmental stress is reported and several of its molecular, mechanistic components are described, providing a tractable platform for future epigenetics experiments. Our findings suggest epigenetic regulation of stomatal development that allows for anatomical and phenotypic plasticity, and may help to explain at least some of the plant’s resilience to fluctuating relative humidity.
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A favoured method of assimilating information from state-of-the-art climate models into integrated assessment models of climate impacts is to use the transient climate response (TCR) of the climate models as an input, sometimes accompanied by a pattern matching approach to provide spatial information. More recent approaches to the problem use TCR with another independent piece of climate model output: the land-sea surface warming ratio (φ). In this paper we show why the use of φ in addition to TCR has such utility. Multiple linear regressions of surface temperature change onto TCR and φ in 22 climate models from the CMIP3 multi-model database show that the inclusion of φ explains a much greater fraction of the inter-model variance than using TCR alone. The improvement is particularly pronounced in North America and Eurasia in the boreal summer season, and in the Amazon all year round. The use of φ as the second metric is beneficial for three reasons: firstly it is uncorrelated with TCR in state-of-the-art climate models and can therefore be considered as an independent metric; secondly, because of its projected time-invariance, the magnitude of φ is better constrained than TCR in the immediate future; thirdly, the use of two variables is much simpler than approaches such as pattern scaling from climate models. Finally we show how using the latest estimates of φ from climate models with a mean value of 1.6—as opposed to previously reported values of 1.4—can significantly increase the mean time-integrated discounted damage projections in a state-of-the-art integrated assessment model by about 15 %. When compared to damages calculated without the inclusion of the land-sea warming ratio, this figure rises to 65 %, equivalent to almost 200 trillion dollars over 200 years.
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This paper investigates the regional characteristics of Indian manufacturing industry. Its aim is to assess whether geography plays any major role in determining the performance or characteristics of Indian manufacturing firms, and in order to do this, it presents the results of cross-section regressions estimated on the basis of a balanced sample of 1607 firms across the 30 Indian states. The results suggest that firm performance and characteristics are related to many of the expected industrial organization variables. However, there is also evidence of significant region–state influences on both the performance and characteristics of Indian manufacturing industry. As such, the results demonstrate that analyses which focus solely on standard non-spatial industrial organization variables will fail to explain much of the cross-sectional variation in firm performance and characteristics. In particular, while there are no systematic simple centre–periphery variations in the Indian regional economic system, there is evidence to suggest that industrial spatial concentration, regional specialization, and regional market size play a key role in determining the performance and characteristics of Indian manufacturing industry.
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The relationship between price volatility and competition is examined. Atheoretic, vector auto regressions on farm prices of wheat and retail prices of derivatives (flour, bread, pasta, bulgur and cookies) are compared to results from a dynamic, simultaneous-equations model with theory-based farm-to-retail linkages. Analytical results yield insights about numbers of firms and their impacts on demand- and supply-side multipliers, but the applications to Turkish time series (1988:1-1996:12) yield mixed results.
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The facilitation of healthier dietary choices by consumers is a key element of government strategies to combat the rising incidence of obesity in developed and developing countries. Public health campaigns to promote healthier eating often target compliance with recommended dietary guidelines for consumption of individual nutrients such as fats and added sugars. This paper examines the association between improved compliance with dietary guidelines for individual nutrients and excess calorie intake, the most proximate determinant of obesity risk. We apply quantile regressions and counterfactual decompositions to cross-sectional data from the National Diet and Nutrition Survey (2000-01) to assess how excess calorie consumption patterns in the UK are likely to change with improved compliance with dietary guidelines. We find that the effects of compliance vary significantly across different quantiles of calorie consumption. Our results show that compliance with dietary guidelines for individual nutrients, even if successfully achieved, is likely to be associated with only modest shifts in excess calorie consumption patterns. Consequently, public health campaigns that target compliance with dietary guidelines for specific nutrients in isolation are unlikely to have a significant effect on the obesity risk faced by the population.
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Historic geomagnetic activity observations have been used to reveal centennial variations in the open solar flux and the near-Earth heliospheric conditions (the interplanetary magnetic field and the solar wind speed). The various methods are in very good agreement for the past 135 years when there were sufficient reliable magnetic observatories in operation to eliminate problems due to site-specific errors and calibration drifts. This review underlines the physical principles that allow these reconstructions to be made, as well as the details of the various algorithms employed and the results obtained. Discussion is included of: the importance of the averaging timescale; the key differences between “range” and “interdiurnal variability” geomagnetic data; the need to distinguish source field sector structure from heliospherically-imposed field structure; the importance of ensuring that regressions used are statistically robust; and uncertainty analysis. The reconstructions are exceedingly useful as they provide calibration between the in-situ spacecraft measurements from the past five decades and the millennial records of heliospheric behaviour deduced from measured abundances of cosmogenic radionuclides found in terrestrial reservoirs. Continuity of open solar flux, using sunspot number to quantify the emergence rate, is the basis of a number of models that have been very successful in reproducing the variation derived from geomagnetic activity. These models allow us to extend the reconstructions back to before the development of the magnetometer and to cover the Maunder minimum. Allied to the radionuclide data, the models are revealing much about how the Sun and heliosphere behaved outside of grand solar maxima and are providing a means of predicting how solar activity is likely to evolve now that the recent grand maximum (that had prevailed throughout the space age) has come to an end.
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NO2 measurements during 1990–2007, obtained from a zenith-sky spectrometer in the Antarctic, are analysed to determine the long-term changes in NO2. An atmospheric photochemical box model and a radiative transfer model are used to improve the accuracy of determination of the vertical columns from the slant column measurements, and to deduce the amount of NOy from NO2. We find that the NO2 and NOy columns in midsummer have large inter-annual variability superimposed on a broad maximum in 2000, with little or no overall trend over the full time period. These changes are robust to a variety of alternative settings when determining vertical columns from slant columns or determining NOy from NO2. They may signify similar changes in speed of the Brewer-Dobson circulation but with opposite sign, i.e. a broad minimum around 2000. Multiple regressions show significant correlation with solar and quasi-biennial-oscillation indices, and weak correlation with El Nino, but no significant overall trend, corresponding to an increase in Brewer-Dobson circulation of 1.4±3.5%/decade. There remains an unexplained cycle of amplitude and period at least 15% and 17 years, with minimum speed in about 2000.
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Purpose – Commercial real estate is a highly specific asset: heterogeneous, indivisible and with less information transparency than most other commonly held investment assets. These attributes encourage the use of intermediaries during asset acquisition and disposal. However, there are few attempts to explain the use of different brokerage models (with differing costs) in different markets. This study aims to address this gap. Design/methodology/approach – The study analyses 9,338 real estate transactions in London and New York City from 2001 to 2011. Data are provided by Real Capital Analytics and cover over $450 billion of investments in this period. Brokerage trends in the two cities are compared and probit regressions are used to test whether the decision to transact with broker representation varies with investor or asset characteristics. Findings – Results indicate greater use of brokerage in London, especially by purchasers. This persists when data are disaggregated by sector, time or investor type, pointing to the role of local market culture and institutions in shaping brokerage models and transaction costs. Within each city, the nature of the investors involved seems to be a more significant influence on broker use than the characteristics of the assets being traded. Originality/value – Brokerage costs are the single largest non-tax charge to an investor when trading commercial real estate, yet there is little research in this area. This study examines the role of brokers and provides empirical evidence on factors that influence the use and mode of brokerage in two major investment destinations.
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Blood lipid response to a given dietary intervention could be determined by the effect of diet, gene variants or gene–diet interactions. The objective of the present study was to investigate whether variants in presumed nutrient-sensitive genes involved in lipid metabolism modified lipid profile after weight loss and in response to a given diet, among overweight European adults participating in the Diet Obesity and Genes study. By multiple linear regressions, 240 SNPs in twenty-four candidate genes were investigated for SNP main and SNP–diet interaction effects on total cholesterol, LDL-cholesterol, HDL-cholesterol and TAG after an 8-week low-energy diet (only main effect), and a 6-month ad libitum weight maintenance diet, with different contents of dietary protein or glycaemic index. After adjusting for multiple testing, a SNP–dietary protein interaction effect on TAG was identified for lipin 1 (LPIN1) rs4315495, with a decrease in TAG of − 0·26 mmol/l per A-allele/protein unit (95 % CI − 0·38, − 0·14, P= 0·000043). In conclusion, we investigated SNP–diet interactions for blood lipid profiles for 240 SNPs in twenty-four candidate genes, selected for their involvement in lipid metabolism pathways, and identified one significant interaction between LPIN1 rs4315495 and dietary protein for TAG concentration.
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This thesis is concerned with development of improved management practices in indigenous chicken production systems in a research process that includes participatory approaches with smallholder farmers and other stakeholders in Kenya. The research process involved a wide range of activities that included on-station experiments, field surveys, stakeholder consultations in workshops, seminars and visits, and on-farm farmer participatory research to evaluate the effect of some improved management interventions on production performance of indigenous chickens. The participatory research was greatly informed from collective experiences and lessons of the previous activities. The on-station studies focused on hatching, growth and nutritional characteristics of the indigenous chickens. Four research publications from these studies are included in this thesis. Quantitative statistical analyses were applied and they involved use of growth models estimated with non-linear regressions for the growth characteristics, chi-square determinations to investigate differences among different reciprocal crosses of indigenous chickens and general linear models and covariance determination for the nutrition study. The on-station studies brought greater understanding of performance and production characteristics of indigenous chickens and the influence of management practices on these characteristics. The field surveys and stakeholder consultations helped in understanding the overarching issues affecting the productivity of the indigenous chickens systems and their place in the livelihoods of smallholder farmers. These activities created strong networking opportunities with stakeholders from a wide spectrum. The on-farm farmer participatory research involved selection of 200 farmers in five regions followed by training and introduction of interventions on improved management practices which included housing, vaccination, deworming and feed supplementation. Implementation and monitoring was mainly done by individual farmers continuously for close to one and half years. Six quarterly visits to the farms were made by the research team to monitor and provide support for on-going project activities. The data collected has been analysed for 5 consecutive 3-monthly periods. Descriptive and inferential statistics were applied to analyse the data collected involving treatment applications, production characteristics and flock demography characteristics. Out of the 200 farmers initially selected, 173 had records on treatment applications and flock demography characteristics while 127 farmers had records on production characteristics. The demographic analysis with a dissimilarity index of flock size produced 7 distinct farm groups from among the 173 farms. Two of these farm groups were represented in similar numbers in each of the five regions. The research process also involved a number of dissemination and communication strategies that have brought the process and project outcomes into the domain of accessibility by wider readership locally and globally. These include workshops, seminars, field visits and consultations, local and international conferences, electronic conferencing, publications and personal communication via emailing and conventional posting. A number of research and development proposals were also developed based on the knowledge and experiences gained from the research process. The thesis captures the research process activities and outcomes in 8 chapters which include in ascending order – introduction, theoretical concepts underpinning FPR, research methodology and process, on-station research output, FPR descriptive statistical analysis, FPR inferential statistical analysis on production characteristics, FPR demographic analysis and conclusions. Various research approaches both quantitative and qualitative have been applied in the research process indicating the possibilities and importance of combining both systems for greater understanding of issues being studied. In our case, participatory studies of the improved management of indigenous chickens indicates their potential importance as livelihood assets for poor people.
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What determines the emergence and survival of democracy? The authors apply extreme bounds analysis to test the robustness of fifty-nine factors proposed in the literature, evaluating over three million regressions with data from 165 countries from 1976 to 2002. The most robust determinants of the transition to democracy are gross domestic product (GDP) growth (a negative effect), past transitions (a positive effect), and Organisation for Economic Co-operation and Development membership (a positive effect). There is some evidence that fuel exporters and Muslim countries are less likely to see democracy emerge, although the latter finding is driven entirely by oil-producing Muslim countries. Regarding the survival of democracy, the most robust determinants are GDP per capita (a positive effect) and past transitions (a negative effect). There is some evidence that having a former military leader as the chief executive has a negative effect, while having other democracies as neighbors has a reinforcing effect.
Resumo:
We assess the robustness of previous findings on the determinants of terrorism. Using extreme bound analysis, the three most comprehensive terrorism datasets, and focusing on the three most commonly analyzed aspects of terrorist activity, i.e., location, victim, and perpetrator, we re-assess the effect of 65 proposed correlates. Evaluating around 13.4 million regressions, we find 18 variables to be robustly associated with the number of incidents occurring in a given country-year, 15 variables with attacks against citizens from a particular country in a given year, and six variables with attacks perpetrated by citizens of a particular country in a given year.
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Many previous studies have shown that unforced climate model simulations exhibit decadal-scale fluctuations in the Atlantic meridional overturning circulation (AMOC), and that this variability can have impacts on surface climate fields. However, the robustness of these surface fingerprints across different models is less clear. Furthermore, with the potential for coupled feedbacks that may amplify or damp the response, it is not known whether the associated climate signals are linearly related to the strength of the AMOC changes, or if the fluctuation events exhibit nonlinear behaviour with respect to their strength or polarity. To explore these questions, we introduce an objective and flexible method for identifying the largest natural AMOC fluctuation events in multicentennial/multimillennial simulations of a variety of coupled climate models. The characteristics of the events are explored, including their magnitude, meridional coherence and spatial structure, as well as links with ocean heat transport and the horizontal circulation. The surface fingerprints in ocean temperature and salinity are examined, and compared with the results of linear regression analysis. It is found that the regressions generally provide a good indication of the surface changes associated with the largest AMOC events. However, there are some exceptions, including a nonlinear change in the atmospheric pressure signal, particularly at high latitudes, in HadCM3. Some asymmetries are also found between the changes associated with positive and negative AMOC events in the same model. Composite analysis suggests that there are signals that are robust across the largest AMOC events in each model, which provides reassurance that the surface changes associated with one particular event will be similar to those expected from regression analysis. However, large differences are found between the AMOC fingerprints in different models, which may hinder the prediction and attribution of such events in reality.