Academic literature on the topic 'Applied Econometrics'

The first essay of this dissertation studies the determinants and effects of firms' participation in a voluntary pollution reduction program (VPR) initiated by government regulators. This research presents empirical evidence in support of the "enforcement theory" for VPRs, which predicts that (1) participation is rewarded by relaxed regulatory scrutiny; (2) the anticipation of this reward spurs firms to participate in the program; and (3) the program rewards regulators with reduced pollution. The results also indicate that firms' VPR participation, and pollutant reductions themselves, were prompted by a firm's likelihood of becoming a boycott target and/or being subject to environmental interest group lobbying for tighter standards.In the second essay, a nonparametric regression estimator which can accommodate two empirically relevant data environments is proposed. The first data environment assumes that at least one of the explanatory variables is discrete. In such an environment, a "cell" approach which estimates a separate regression for each discrete cell, has generally been employed. The second data environment assumes that one needs to estimate a set of regression functions that belong to different individuals. In both environments the proposed estimator attempts to reduce estimation error by incorporating extraneous data from the other individuals or "cells" when estimating the regression function for a given individual or "cell". The simulation results for the proposed estimator demonstrate a strong potential in empirical applications.In the third essay, the nonparametric approach proposed in the second essay is used to estimate the parameters of the short-term interest rate diffusion. The nonparametric estimators of the drift of the short rate proposed by Stanton (1997) and Jiang (1998) can produce spurious nonlinearities due to the persistent dependence and limited sampling period of interest rates. The simulations show that the proposed estimator significantly attenuates the spurious nonlinearities of Stanton's nonparametric estimator. An empirical study of the US term structure of interest rates is presented based on the proposed estimator and two other competing models. The results suggest that the estimation of the short rate diffusion parameters using additional data from yields of different maturities has significant economic implications on the valuation interest rate derivatives.

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Economics, 2016.<br>Cataloged from PDF version of thesis. "with Eric Sodomka and Nicolas E. Stier-Moses"--Page 6 [Below title of Chapter 1].<br>Includes bibliographical references.<br>Chapter 1 focuses on the problem of predicting equilibrium outcomes in large online auction markets. For online retailers, content publishers, and search engines, predicting how the behavior of their auction markets might respond to policy changes is an important business problem. However, this problem is challenging due to both the size and the complexity of such real-world markets. We introduce a method for predicting how various statistics of such markets adjust to changes in supply and demand by: (1) modeling the auction market mechanism as a Walrasian mechanism, (2) coarsening the resulting Walrasian market via a stochastic block model, (3) computing the Walrasian equilibrium of this coarsened market through sampling, and (4) using the resulting equilibrium, together with some reduced-form adjustments, to approximate the equilibrium of the initial auction market. We demonstrate the internal consistency of this method through formal proofs and synthetic experiments, and demonstrates its accuracy by comparison with the equilibrium outcomes of a more realistic pacing-based model of auction markets. Chapter 2 introduces a model of consumer choice in which consumers simplify their latent high-dimensional preference vector into a low-dimensional one used for choosing products. This assumption induces a particular population structure over consumers' simplified preferences, which allows for tractable estimation in high dimensional settings. Estimation is performed via a stochastic gradient descent-based algorithm, and we evaluate its performance through a variety synthetic benchmarks. We also estimate the model on consumer consideration data, finding that the average consumer uses only 6 of 16 product attributes when forming their consideration set, and that this leads to a utility of loss of 2 - 3% on average. Chapter 3 uses admissions data from the University of Bologna's medical school to analyze how students' entrance exam rankings affect their subsequent academic performance. We find that: (1) worse rankings lead to worse academic performance, (2) this impact is more negative for worse-ranked students, (3) this impact on academic performance operates mostly through courseload rather than through GPA, and (4) male and female students' academic performance do not respond differentially to rank.<br>by J. Mark Hou.<br>Ph. D.

Submitted by Rafael Burjack Farias Duarte (burjack86@gmail.com) on 2016-04-08T00:01:56Z No. of bitstreams: 1 Final_bib.pdf: 5471404 bytes, checksum: 29bf9321d29ec324d42b89681de3eb28 (MD5)<br>Approved for entry into archive by GILSON ROCHA MIRANDA (gilson.miranda@fgv.br) on 2016-06-02T16:47:53Z (GMT) No. of bitstreams: 1 Final_bib.pdf: 5471404 bytes, checksum: 29bf9321d29ec324d42b89681de3eb28 (MD5)<br>Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2016-06-13T18:12:59Z (GMT) No. of bitstreams: 1 Final_bib.pdf: 5471404 bytes, checksum: 29bf9321d29ec324d42b89681de3eb28 (MD5)<br>Made available in DSpace on 2016-06-13T18:13:41Z (GMT). No. of bitstreams: 1 Final_bib.pdf: 5471404 bytes, checksum: 29bf9321d29ec324d42b89681de3eb28 (MD5) Previous issue date: 2015-11-27<br>Using a unique dataset on Brazilian nominal and real yield curves combined with daily survey forecasts of macroeconomic variables such as GDP growth, inflation, and exchange rate movements, we identify the effect of surprises to the Brazilian interbank target rate on expected future nominal and real short rates, term premia, and inflation expectations. We find that positive surprises to target rates lead to higher expected nominal and real interest rates and reduced nominal and inflation term premia. We also find a strongly positive relation between both real and nominal term premia and measures of dispersion in survey forecasts. Uncertainty about future exchange rates is a particularly important driver of variations in Brazilian term premia.

This thesis is divided in three essays. The first essay examines the reactions by incumbent airhnes to the threat and actual entry of the low-cost carrier Gol in the Brazilian domestic air transport market. By estimating the reactions in prices, quantities and supply variables, it investigates the plausibility of theories of entry deterrence and accommodation. The second essay proposes and implements a parsimonious three-factor model of the term structure whose dynamics is driven uniquely by observable state variables. The method allows comparing alternative views on the way state variables - macroeconomic variables, in particular - influence the yield curve dynamics, avoids curse of dimensionality problems commonly appearing in traditional models, and provides more reliable inference by using both the cross-sectional and the time series dimension of the data. I conduct in- and out-of-sample studies using a comprehensive set of US data. I show that even a parsimonious model where the level, slope and curvature factors of the term structure are driven by, respectively, measures of inflation, monetary policy and economic activity consistently outperforms the (latent-variable) benchmark model out-of-sample, when considering the five NBER-dated recessions of the last three decades. In the third essay I empirically evaluate the incentives to tacitly collude in differentiated product markets. Tacit collusion plays an important role in merger policy: competition agencies sometimes block mergers on the grounds that they will generate 'coordinated effects', an increased likelihood of collusion. I thus propose an approach to coordinated effects merger simulation in markets where multi-product firms operate in differentiated product markets. To the best of my knowledge, this is the first full empirical implementation of a coordinated effects merger simulation model in a differentiated product market. I use the model to study the network server market and, specifically, examine the effect of the merger between HP and Compaq on their and their rivals' collective incentives and ability to sustain tacit collusion. The results suggest that the incentives to collude in the network server market are substantial, but actively decreased following the merger between HP and Compaq. In addition to exploring the incentives for collusion on one market I also examine the impact of (i) multi-market contact on firms' incentive and ability to sustain tacit coordination and (ii) a competitive fringe of smaller players who co-exist with a subset of the larger players in an industry who tacitly collude. By taking the economic theory of tacit collusion seriously in an empirical example, I show that the intuition many economists have for the effect of mergers on the incentives to tacitly collude is actually wrong.

Submitted by Ana Flávia Soares dos Santos (anaflavia1611@hotmail.com) on 2018-07-19T16:58:08Z No. of bitstreams: 1 essays_in_applied_econometrics_and_monpolicy.pdf: 1666665 bytes, checksum: 2a17b26565699261b38351020ad9f710 (MD5)<br>Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2018-08-27T18:39:29Z (GMT) No. of bitstreams: 1 essays_in_applied_econometrics_and_monpolicy.pdf: 1666665 bytes, checksum: 2a17b26565699261b38351020ad9f710 (MD5)<br>Made available in DSpace on 2018-08-27T19:19:05Z (GMT). No. of bitstreams: 1 essays_in_applied_econometrics_and_monpolicy.pdf: 1666665 bytes, checksum: 2a17b26565699261b38351020ad9f710 (MD5) Previous issue date: 2018-06-19<br>This thesis contains three independent chapters. The first one is about central bank credibility, where we measure people’s beliefs using survey data on inflation expectations and focus on the 12-month-ahead horizon since it is widely used in the literature. Beliefs are measured by employing the panel-data setup of Gaglianone and Issler (2015), who show that optimal individual forecasts are an affine function of one factor alone – the conditional expectation of inflation. This allows the identification and estimation of the common factor, our measure of people’s beliefs. Second, we compare beliefs with explicit (or tacit) targets by constructing Heteroskedasticity and Autocorrelation Consistent (HAC) 95% asymptotic confidence intervals for our estimates of the conditional expectation of inflation, which is an original contribution of this paper. Whenever the target falls into this interval we consider the central bank credible. We consider it not credible otherwise. This approach is applied to the issue of credibility of the Central Bank of Brazil (BCB) by using the now well-known Focus Survey of forecasts, kept by the BCB on inflation expectations, from January 2007 until April 2017. Results show that the BCB was credible 65% of the time, with the exception of a few months in the beginning of 2007 and during the interval between mid-2013 throughout mid-2016. We also constructed a credibility index for this period and compared it with alternative measures of credibility. In the second chapter, we show that it is possible to conciliate individual and consensus rationality tests, by developing a new framework to test for rational expectations hypothesis. We propose a methodology that verifies the consistency of the above mentioned expectation formation rule, where we explicitly allow for the possibility of heterogeneous expectations at the individual level, but also keeping individual and consensus expectations at the same system. We advance with respect to Keane and Runkle (1990)’s previous work, which argued that almost all existing tests in the literature so far were either incorrect or inadequate. In the third chapter, we propose an individual coincident indicator for the following Latin American countries: Argentina, Brazil, Chile, Colombia and Mexico. In order to obtain similar series to those traditionally used in business-cycle research in constructing coincident indices (output, sales, income and employment) we backcast several individual country series which were not available in a long time-series span. We also establish a chronology of recessions for these countries, covering the period from 1980 to 2012 on a monthly basis. Based on this chronology, the countries are compared in several respects. The final contribution is to propose an aggregate coincident indicator for the Latin American economy, which weights individualcountry composite indices. Finally, this indicator is compared with the coincident indicator (The Conference Board – TCB) of the U.S. economy. We find that the U.S. indicator Granger-causes the Latin American indicator in statistical tests.

This thesis presents three essays in the field of applied econometrics. In the first essay, we use the establishment-level Annual Respondents Database (ARD) data and the sector-level Confederation of British Industry (CBI) Industrial Trends Survey data to identify the key determinants of U.K. manufacturing investment. We first examine the trends in the ARD microdata aggregates, the relative price of investment goods data, and the CBI survey data. Subsequently, we estimate a baseline dynamic error correction investment model which separates out short-run and long-run investment dynamics. When we introduce additional variables derived from the CBI survey data to the baseline model, the estimation results show that survey variables pertaining to financing constraints and demand uncertainty have negative effects on investment, while the survey variable related to the volume of total new orders has a positive effect on investment. In the second essay, we develop forecasting models for aggregate U.K. manufacturing investment. After assessing the CBI's forecasting record over the recent financial crisis, we conclude that CBI forecasters were slow in realizing the severe negative effect of the credit crisis on manufacturing investment. Subsequently, we develop our own baseline error-correction forecasting model, which conditions only on lagged explanatory variables, and apply the general-to-specific modeling approach to simplify the model. However, the selected baseline specification has poor out-of-sample forecast properties over the crisis period. When we include additional CBI survey variables in the baseline model, there is an improvement in the out-ofsample forecast performance in most cases. Survey measures of business optimism and expected future demand are found to be particularly useful in this context. Finally, in the third essay, we employ a Threshold Vector Autoregression (TVAR) model to examine the potentially nonlinear impact of fiscal stimulus on output under tight and loose credit supply conditions in the U.S. In our main specification, we choose the excess bond premium as the threshold variable to identify periods of tight credit and loose credit. The empirical results suggest that government spending increases are more effective at stimulating output than tax cuts, especially when credit conditions are loose.