How Do Changes In Gasoline Prices Affect Bus Ridership In The Twin Cities?,
2016
Macalester College
How Do Changes In Gasoline Prices Affect Bus Ridership In The Twin Cities?, Kim Eng Ky
Economics Honors Projects
What determines the likelihood a resident will take public transit? To understand the relative effects of various determinants of ridership, this study focuses on the effects of gasoline prices, controlling for other determinants such as number of workdays in a given month, traffic, unemployment rate, and service quality. As gasoline prices increase, it becomes more expensive to drive a car. Thus, customers would likely shy away from driving and substitute towards the alternatives; one of which is public transportation. This study aims to find the relationship between gasoline prices and bus ridership at a disaggregated level (route type level) in …
Disentangling Greenhouse Warming And Aerosol Cooling To Reveal Earth's Climate Sensitivity,
2016
Yale University
Disentangling Greenhouse Warming And Aerosol Cooling To Reveal Earth's Climate Sensitivity, T. Storelvmo, T. Leirvik, U. Lohmann, Peter C. B. Phillips, M. Wild
Research Collection School Of Economics
Earth's climate sensitivity has long been subject to heated debate and has spurred renewed interest after the latest IPCC assessment report suggested a downward adjustment of its most likely range(1). Recent observational studies have produced estimates of transient climate sensitivity, that is, the global mean surface temperature increase at the time of CO2 doubling, as low as 1.3 K (refs 2,3), well below the best estimate produced by global climate models (1.8 K). Here, we present an observation-based study of the time period 1964 to 2010, which does not rely on climate models. The method incorporates observations of greenhouse gas …
Rhode Island Current Conditions Index -- March 2016,
2016
University of Rhode Island
Rhode Island Current Conditions Index -- March 2016, Leonard Lardaro
The Rhode Island Current Conditions Index
No abstract provided.
Asymptotic Power Of The Sphericity Test Under Weak And Strong Factors In A Fixed Effects Panel Data Model,
2016
Syracuse University
Asymptotic Power Of The Sphericity Test Under Weak And Strong Factors In A Fixed Effects Panel Data Model, Badi H. Baltagi, Chihwa Kao, Fa Wang
Center for Policy Research
This paper studies the asymptotic power for the sphericity test in a fixed effect panel data model proposed by Baltagi, Feng and Kao (2011), (JBFK). This is done under the alternative hypotheses of weak and strong factors. By weak factors, we mean that the Euclidean norm of the vector of the factor loadings is O(1). By strong factors, we mean that the Euclidean norm of the vector of factor loadings is O(pn), where n is the number of individuals in the panel. To derive the limiting distribution of JBFK under the alternative, we first derive the limiting distribution of its …
The Impact Of Lending Rate On The Manufacturing Sector In Nigeria,
2016
Central Bank of Nigeria
The Impact Of Lending Rate On The Manufacturing Sector In Nigeria, D. B. Akpan, D. J. Yilkudi, D. C. Opiah
Economic and Financial Review
The study investigates the impact of lending rate on output of the manufacturing subsector using the Vector Error Correction Model (VECM) and annual data from 1981- 2014. The empirical results indicated that high lending rate had negative impact on manufacturing output in the long-run. This suggests that increase in lending rate undermines manufacturing output, thus retarding growth in the real sector. Specifically, the estimates revealed that a 1.0 per cent increase in lending rate reduces manufacturing output by 0.03 per cent. The study, therefore, recommends the implementation of investment friendly policies that narrows the lending rate by the deposit money …
Shrinkage Estimation Of Common Breaks In Panel Data Models Via Adaptive Group Fused Lasso,
2016
Shanghai Jiaotong University
Shrinkage Estimation Of Common Breaks In Panel Data Models Via Adaptive Group Fused Lasso, Junhui Qian, Liangjun Su
Research Collection School Of Economics
In this paper we consider estimation and inference of common breaks in panel data models via adaptive group fused Lasso. We consider two approaches—penalized least squares (PLS) for first-differenced models without endogenous regressors, and penalized GMM (PGMM) for first-differenced models with endogeneity. We show that with probability tending to one, both methods can correctly determine the unknown number of breaks and estimate the common break dates consistently. We establish the asymptotic distributions of the Lasso estimators of the regression coefficients and their post Lasso versions. We also propose and validate a data-driven method to determine the tuning parameter used in …
Prices, Markups, And Trade Reform,
2016
Princeton University
Prices, Markups, And Trade Reform, Jan De Loecker, Pinelopi K. Goldberg, Amit K. Khandelwal, Nina Pavcnik
Dartmouth Scholarship
This paper examines how prices, markups, and marginal costs respond to trade liberalization. We develop a framework to estimate markups from production data with multi‐product firms. This approach does not require assumptions on the market structure or demand curves faced by firms, nor assumptions on how firms allocate their inputs across products. We exploit quantity and price information to disentangle markups from quantity‐based productivity, and then compute marginal costs by dividing observed prices by the estimated markups. We use India's trade liberalization episode to examine how firms adjust these performance measures. Not surprisingly, we find that trade liberalization lowers factory‐gate …
Estimation Of Large Dimensional Factor Models With An Unknown Number Of Breaks,
2016
University of California, Riverside
Estimation Of Large Dimensional Factor Models With An Unknown Number Of Breaks, Shujie Ma, Liangjun Su
Research Collection School Of Economics
In this paper we study the estimation of a large dimensional factor model when the factor loadings exhibit an unknown number of changes over time. We propose a novel three-step procedure to detect the breaks if any and then identify their locations. In the first step, we divide the whole time span into subintervals and fit a conventional factor model on each interval. In the second step, we apply the adaptive fused group Lasso to identify intervals containing a break. In the third step, we devise a grid search method to estimate the location of the break on each identified …
Model Selection For Explosive Models,
2016
Singapore Management University
Model Selection For Explosive Models, Yubo Tao, Jun Yu
Research Collection School Of Economics
This paper examines the limit properties of information criteria for distinguishing between the unit root model and the various kinds of explosive models. The information criteria include AIC, BIC, HQIC. The explosive models include the local-to-unit-root model, the mildly explosive model and the regular explosive model. Initial conditions with different order of magnitude are considered. Both the OLS estimator and the indirect inference estimator are studied. It is found that BIC and HQIC, but not AIC, consistently select the unit root model when data come from the unit root model. When data come from the local-to-unit-root model, both BIC and …
Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models,
2016
Singapore Management University
Sieve Instrumental Variable Quantile Regression Estimation Of Functional Coefficient Models, Liangjun Su, Tadao Hoshino
Research Collection School Of Economics
In this paper we consider sieve instrumental variable quantile regression (IVQR) estimation of functional coefficient models where the coefficients of endogenous regressors are unknown functions of some exogenous covariates. We estimate the functional coefficients by the sieve-IVQR technique and establish the uniform consistency and asymptotic normality of the estimators. Based on the sieve estimates, we propose a nonparametric specification test for the constancy of the functional coefficients and study its asymptotic. We conduct simulations to evaluate the finite sample behavior of our estimator and test statistic, and apply our method to study the estimation of quantile Engel curves.
The Effects Of Alcohol Use On Economic Decision Making,
2016
University of Arkansas
The Effects Of Alcohol Use On Economic Decision Making, Klajdi Bregu, Cary Deck, Lindsay Ham, Salar Jahedi
ESI Working Papers
It is notoriously hard to study the effect of alcohol on decision making, given the selection that takes place in who drinks alcohol and when they choose to do so. In a controlled laboratory experiment, we study the causal effect of alcohol on economic decision making. We examine the impact of alcohol on the following types of tasks: math and logic, uncertainty, overconfidence, strategic games, food choices, anchoring, and altruism. Our results indicate that alcohol consumption, as measured by the blood alcohol concentration (BAC), increases cooperation in strategic settings and altruism in Dictator games. We do not find any effects …
Optimal Tilts,
2016
Harvard Business School
Optimal Tilts, Malcom Baker, Terence C. Burnham, Ryan Taliaferro
ESI Working Papers
We examine the optimal weighting of four characteristic tilts in US equity markets over the period from 1968 through 2014. We define a “tilt” as a positive-Sharpe-ratio, characteristicbased portfolio strategy that requires relatively low annual turnover and a “trade” as a characteristic-based portfolio strategy that requires relatively high annual turnover and liquidity demands. Size is a tilt, because of its very low turnover; high frequency reversal is a trade. This dichotomy is necessary to make practical use of Fama-French style factor regressions. Unlike low-turnover tilts, a full history of transaction costs and an estimate of capacity is critical to determine …
Rhode Island Current Conditions Index -- February 2016,
2016
University of Rhode Island
Rhode Island Current Conditions Index -- February 2016, Leonard Lardaro
The Rhode Island Current Conditions Index
No abstract provided.
Prediction In A Generalized Spatial Panel Data Model With Serial Correlation,
2016
Syracuse University
Prediction In A Generalized Spatial Panel Data Model With Serial Correlation, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper considers the generalized spatial panel data model with serial correlation proposed by Lee and Yu (2012) which encompasses a lot of the spatial panel data models considered in the literature, and derives the best linear unbiased predictor (BLUP) for that model. This in turn provides valuable BLUP for several spatial panel models as special cases.
Testing For Monotonicity In Unobservables Under Unconfoundedness,
2016
Boston College
Testing For Monotonicity In Unobservables Under Unconfoundedness, Stefan Hoderlein, Liangjun Su, Halbert White, Thomas Tao Yang
Research Collection School Of Economics
Monotonicity in a scalar unobservable is a common assumption when modeling heterogeneity in structural models. Among other things, it allows one to recover the underlying structural function from certain conditional quantiles of observables. Nevertheless, monotonicity is a strong assumption and in some economic applications unlikely to hold, e.g., random coefficient models. Its failure can have substantive adverse consequences, in particular inconsistency of any estimator that is based on it. Having a test for this hypothesis is hence desirable. This paper provides such a test for cross-section data. We show how to exploit an exclusion restriction together with a conditional independence …
Firms' Decisions To Enter A Market Of Highly Differentiated Products: Apparel Industry And New York Fashion Week,
2016
CUNY Graduate Center
Firms' Decisions To Enter A Market Of Highly Differentiated Products: Apparel Industry And New York Fashion Week, Yoko Katagiri
Dissertations, Theses, and Capstone Projects
This dissertation deals with economic aspects of the fashion industry. It begins with a discussion of the complex industrial organization aspects of the industry. A wealth of information in this area has been assembled and is presented for the first time. The focus is on the high-end fashion market: how it started, how it works, New York Fashion Week, and its significance for the industry. Then a comprehensive review of the economics literature as it pertains to the industry is presented, also for the first time. The empirical sections of the dissertation contain estimates of demand functions for apparel and …
Granger Causality And Structural Causality In Cross-Section And Panel Data,
2016
Hong Kong University of Science and Technology
Granger Causality And Structural Causality In Cross-Section And Panel Data, Xun Lu, Liangjun Su, Halbert White
Research Collection School Of Economics
Granger non-causality in distribution is fundamentally a probabilistic conditional independence notion that can be applied not only to time series data but also to cross-section and panel data. In this paper, we provide a natural definition of structural causality in cross-section and panel data and forge a direct link between Granger (G-) causality and structural causality under a key conditional exogeneity assumption. To put it simply, when structural effects are well defined and identifiable, G- non-causality follows from structural non-causality, and with suitable conditions (e.g., separability or monotonicity), structural causality also implies G-causality. This justifies using tests of G- non-causality …
Common Threshold In Quantile Regressions With An Application To Pricing For Reputation,
2016
Singapore Management University
Common Threshold In Quantile Regressions With An Application To Pricing For Reputation, Liangjun Su, Pai Xu, Heng Ju
Research Collection School Of Economics
The paper develops a systematic estimation and inference procedure for quantile regression models where there may exist a common threshold effect across different quantile indices. We first propose a sup-Wald test for the existence of a threshold effect, and then study the asymptotic properties of the estimators in a threshold quantile regression model under the shrinking-threshold-effect framework. We consider several tests for the presence of a common threshold value across different quantile indices and obtain their limiting distributions. We apply our methodology to study the pricing strategy for reputation via the use of a dataset from Taobao.com. In our economic …
Arousal And Economic Decision Making,
2016
RAND Corporation
Arousal And Economic Decision Making, Salar Jahedi, Cary Deck, Dan Ariely
ESI Working Papers
Previous experiments have found that subjecting participants to cognitive load leads to poorer decision making, consistent with dual-system models of behavior. Rather than taxing the cognitive system, this paper reports the results of an experiment that takes a complementary approach: arousing the emotional system. The results indicate that exposure to arousing visual stimuli as compared to neutral images has a negligible impact on performance in arithmetic tasks, impatience, risk taking in the domain of losses, and snack choice although we find that arousal modestly increases in risk-taking in the gains domain and increases susceptibility to anchoring effects. We find the …
Who Wants The Right To Know? An Analysis Of Gmo-Labeling In California,
2016
Colby College
Who Wants The Right To Know? An Analysis Of Gmo-Labeling In California, Sylvia M. Xu
Journal of Environmental and Resource Economics at Colby
There are many studies that have been done to examine what types of voting behavior or patterns are present when voting for environmental ballot measures. This paper examines what characteristics of people are likely to cause them to support Proposition 37 in California, an initiative that, if passed, would require GMO-labeling on all genetically modified foods. Using voting data at a zip code level, I use OLS regression to identify specifically what type of political party, education, occupation, household status, and income levels are more likely to support the bill. I also run weighted regressions by population and number of …
