Challenges of Big Data Analysis

Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This article give overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasis on the viability of the sparsest solution in high-confidence set and point out that exogeneous assumptions in most statistical methods for Big Data can not be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions

THE INFLUENCE OF ATTRIBUTE CUTOFFS ON CONSUMERS’ CHOICES OF A FUNCTIONAL FOOD

This study investigates evidence of non-compensatory preferences by incorporating attribute cutoffs into the modeling of consumer choices in the context of food with health-related attributes (omega-3 content) that may be associated with fortification or may result from genetic modification (GM). Data for this study were collected through a nation-wide internet-based survey drawn from a representative panel of Canadian households maintained by a major North American marketing firm. In addition to querying respondents on their perceptions and attitudes regarding food and health, choices of canola oils are elicited using a stated choice experiment in which product alternatives are identified based on attributes of price, country of origin, omega-3 content and GM/non-GM derivation. Consumers’ choices for functional canola oil products are examined in three steps. Initially, a conditional logit (CL) model is estimated assuming that no cutoffs apply in decisions on canola oil choices. Respondent’s self-reported cutoffs are then incorporated into the CL model and a random parameters logit (RPL) model, applying a utility model which penalizes rather than eliminates a desired alternative when a cutoff violation occurs. In the third step, the problem of endogeneity associated with attribute cutoffs is examined by linking respondents’ self-reported cutoffs to their demographic characteristics. Results from estimations of models with/without cutoffs show that consumers value omega-3 content in canola oils but dislike GM-derived ingredients in canola oil products. These Canadian respondents prefer canola oils produced in Canada to those produced in the United States. Regarding attribute cutoffs, it is found that consumers suffer a utility loss when violating their self-reported attribute cutoffs. Comparisons between models with/without attribute cutoffs suggest that incorporating cutoffs into the compensatory utility model significantly improves the model fit. Cutoff endogeneity is examined by predicting cutoffs based on respondents’ demographic characteristics. Using predicted cutoffs as instruments for self-reported cutoffs, this study provides some evidence that self-reported cutoffs may be endogenous and that researchers should consider using approaches that account for the potential endogeneity.decision strategy, attribute cutoff, functional food, Agricultural and Food Policy, Consumer/Household Economics, Demand and Price Analysis, Food Consumption/Nutrition/Food Safety, Food Security and Poverty, Health Economics and Policy, C25, C93, D1,

EVALUATING THE COST EFFECTIVENESS OF LAND RETIREMENT PROGRAMS

This paper extends an integrated framework that combines economic, environmental and GIS modeling to evaluate the cost effectiveness of land retirement programs. The modeling framework is applied to the Lower Sangamon Watershed in Cass County of Illinois to examine the economic costs and environmental benefits of three land retirement scenarios: land actually enrolled in the Illinois CREP, land selected by a land rental cap mechanism and land identified by a least cost model. We find that land retirement in the watershed successfully achieved the program goal of 20% sediment abatement. However, in achieving the same level of sediment abatement, the costs of actual land retirement are 1.3 times and 2.1 times of those in a land rental cap mechanism and a least cost model respectively. The model results also reveal that cost effective land retirement parcels are more sloping, close to river, with higher upland sediment inflow, more on-site erosion and lower quasi-rents. The results indicate that governments may improve the cost effectiveness of land retirement program through targeting. And there is a need to modify current Illinois CREP eligibility criteria to include sloping cropland adjacent to the river in the program. Furthermore our results suggest that in the program implementation land retirement contracts could be selected based on several measurable parameters such as distance from the river and slope.Land Economics/Use,

R&D cooperation and spillovers: Some empirical evidence

Different aspects of external information flows have typically been lumped together under the name "spillovers". We attempt to refine our understanding of external information flows through the construction of firm-specific measures of incoming spillovers and appropriability from survey data on Belgian manufacturing firms. Incoming spillovers measure the importance of publicly available information for the innovation process of the firm. Appropriability is defined as the effectiveness of several protection mechanisms for appropriating the benefits of successful innovations. The importance of this distinction between incoming spillovers and appropriability is revealed when contrasting their effects on different types of cooperative agreements. The decision to cooperate with research institutes is mainly affected by the level of incoming spillovers, while appropriability plays an important role for cooperating with suppliers or customers.Research & development; cooperation; spillovers; appropriability

A Spatial Quantile Regression Hedonic Model of Agricultural Land Prices

Abstract Land price studies typically employ hedonic analysis to identify the impact of land characteristics on price. Owing to the spatial fixity of land, however, the question of possible spatial dependence in agricultural land prices arises. The presence of spatial dependence in agricultural land prices can have serious consequences for the hedonic model analysis. Ignoring spatial autocorrelation can lead to biased estimates in land price hedonic models. We propose using a flexible quantile regression-based estimation of the spatial lag hedonic model allowing for varying effects of the characteristics and, more importantly, varying degrees of spatial autocorrelation. In applying this approach to a sample of agricultural land sales in Northern Ireland we find that the market effectively consists of two relatively separate segments. The larger of these two segments conforms to the conventional hedonic model with no spatial lag dependence, while the smaller, much thinner market segment exhibits considerable spatial lag dependence. Un mod�le h�donique � r�gression quantile spatiale des prix des terrains agricoles R�sum� Les �tudes sur le prix des terrains font g�n�ralement usage d'une analyse h�donique pour identifier l'impact des caract�ristiques des terrains sur le prix. Toutefois, du fait de la fixit� spatiale des terrains, la question d'une �ventuelle d�pendance spatiale sur la valeur des terrains agricoles se pose. L'existence d'une d�pendance spatiale dans le prix des terrains agricoles peut avoir des cons�quences importantes sur l'analyse du mod�le h�donique. En ignorant cette corr�lation s�rielle, on s'expose au risque d'�valuations biais�es des mod�les h�doniques du prix des terrains. Nous proposons l'emploi d'une estimation � base de r�gression flexible du mod�le h�donique � d�calage spatial, tenant compte de diff�rents effets des caract�ristiques, et surtout de diff�rents degr�s de corr�lations s�rielles spatiales. En appliquant ce principe � un �chantillon de ventes de terrains agricoles en Irlande du Nord, nous d�couvrons que le march� se compose de deux segments relativement distincts. Le plus important de ces deux segments est conforme au mod�le h�donique traditionnel, sans d�pendance du d�calage spatial, tandis que le deuxi�me segment du march�, plus petit et beaucoup plus �troit, pr�sente une d�pendance consid�rable du d�calage spatial. Un modelo hed�nico de regresi�n cuantil espacial de los precios del terreno agr�cola Resumen T�picamente, los estudios del precio de la tierra emplean un an�lisis hed�nico para identificar el impacto de las caracter�sticas de la tierra sobre el precio. No obstante, debido a la fijeza espacial de la tierra, surge la cuesti�n de una posible dependencia espacial en los precios del terreno agr�cola. La presencia de dependencia espacial en los precios del terreno agr�cola puede tener consecuencias graves para el modelo de an�lisis hed�nico. Ignorar la autocorrelaci�n espacial puede conducir a estimados parciales en los modelos hed�nicos del precio de la tierra. Proponemos el uso de una valoraci�n basada en una regresi�n cuantil flexible del modelo hed�nico del lapso espacial que tenga en cuenta los diversos efectos de las caracter�sticas y, particularmente, los diversos grados de autocorrelaci�n espacial. Al aplicar este planteamiento a una muestra de ventas de terreno agr�cola en Irlanda del Norte, descubrimos que el mercado consiste efectivamente de dos segmento relativamente separados. El m�s grande de estos dos segmentos se ajusta al modelo hed�nico convencional sin dependencia del lapso espacial, mientras que el segmento m�s peque�o, y mucho m�s fino, muestra una dependencia considerable del lapso espacial.Spatial lag, quantile regression, hedonic model, C13, C14, C21, Q24,

Modelling Spatial Regimes in Farms Technologies

We exploit the information derived from geographical coordinates to endogenously identify spatial regimes in technologies that are the result of a variety of complex, dynamic interactions among site-specific environmental variables and farmer decision making about technology, which are often not observed at the farm level. Controlling for unobserved heterogeneity is a fundamental challenge in empirical research, as failing to do so can produce model misspecification and preclude causal inference. In this article, we adopt a two-step procedure to deal with unobserved spatial heterogeneity, while accounting for spatial dependence in a cross-sectional setting. The first step of the procedure takes explicitly unobserved spatial heterogeneity into account to endogenously identify subsets of farms that follow a similar local production econometric model, i.e. spatial production regimes. The second step consists in the specification of a spatial autoregressive model with autoregressive disturbances and spatial regimes. The method is applied to two regional samples of olive growing farms in Italy. The main finding is that the identification of spatial regimes can help drawing a more detailed picture of the production environment and provide more accurate information to guide extension services and policy makers

The limits of statistical significance of Hawkes processes fitted to financial data

Many fits of Hawkes processes to financial data look rather good but most of them are not statistically significant. This raises the question of what part of market dynamics this model is able to account for exactly. We document the accuracy of such processes as one varies the time interval of calibration and compare the performance of various types of kernels made up of sums of exponentials. Because of their around-the-clock opening times, FX markets are ideally suited to our aim as they allow us to avoid the complications of the long daily overnight closures of equity markets. One can achieve statistical significance according to three simultaneous tests provided that one uses kernels with two exponentials for fitting an hour at a time, and two or three exponentials for full days, while longer periods could not be fitted within statistical satisfaction because of the non-stationarity of the endogenous process. Fitted timescales are relatively short and endogeneity factor is high but sub-critical at about 0.8

The Political Economy: Political Attitudes and Economic Behavior

It has long been recognized that voters bring their political behaviors in line with economic assessments. Recent work, however, suggests that citizens also engage in economic behaviors that align with their confidence—or lack thereof—in the political system. This alignment can happen consciously or, as we suggest, unconsciously, in the same way that positivity carries over to other behaviors on a micro-level. Using monthly time series data from 1978 to 2008, we contribute further evidence of this relationship by demonstrating that political confidence affects consumer behavior at the aggregate level over time. Our analyses employ measures more closely tied to the theoretical concepts of interest while simultaneously accounting for the complex relationships between subjective and objective economic indicators, economic behavior, political attitudes, and the media. Our results suggest that approval of the president not only increases the electorate’s willingness to spend money, but also affects the volatility of this spending. These findings suggest that the economy is influenced by politics beyond elections, and gives the “Chief Economist” another avenue by which they can affect the behavior of the electorate