Topics in Microeconometrics with Applications to Energy

CIDE
XXIII Corso Residenziale di Econometria
9-14 Settembre 2013 - Palermo
Topics in Microeconometrics
with Applications to Energy & Environmental Economics
General Information
Students requiring accommodation will stay at the Hotel President (via F. Crispi, 228). The hotel
is located in the city center, close to the Stazione Marittima. Buses from the airport stop very
close to the hotel (bus stop “Porto”, via E. Amari). The hotel has a very convenient wi-fi
system, which allows participants (25 at maximum), who own a personal computer, to access
their e-mail accounts, to receive class material and to communicate with teachers and
coordinators. On this respect, and in order to obtain maximum benefit from each practical
computer session, it is essential that participants are equipped with their own computers.
Lectures and classes will be held in the nearby Camera di Commercio, which is located at
walking distance from the hotel (via E. Amari 11). Lectures and classes will be scheduled in the
morning (9.00-13.00), as well as in the afternoon (14.30-18.00). Lunch for residents and nonresidential participants will be served in the penthouse of the Hotel President at 13.30.
Participants are kindly requested to gather in the hall of the Hotel President on September 8, at
18.00, where further organizational details will be given, and material used in the course will be
distributed.
Coordinators
Prof. Matteo Manera, Università di Milano-Bicocca (e-mail: [email protected])
Prof. Vincenzo Fazio, Università di Palermo (e-mail: [email protected])
Teachers
Prof. Barbara Chizzolini, Università Bocconi, Milano (e-mail: [email protected])
Prof. Marzio Galeotti, Università di Milano (e-mail: [email protected])
Prof. Matteo Manera, Università di Milano-Bicocca (e-mail: [email protected])
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Course Outline
1st Part
Stationary Panel Data Models
1. Models for pooled time series
1.1. System estimation: SURE
1.2. Model with individual heteroskedasticity and correlation
1.3. Model with individual heteroskedasticity and serial correlation
1.4. Model with individual heteroskedasticity, serial and individual correlation
2. Models for longitudinal data
2.1. Fixed effects model: Within estimator and test for fixed effects
2.2. Random effects model: GLS/FGLS estimator, Between estimator, computation of individual
effects and test for random effects
2.3. Random effects correlated with regressors
3. Models with instrumental variables and two-way models
3.1. Consistent and efficient IV estimators
3.2. Testing the absence of correlation between individual effects and regressors
3.3. Two-way models
4. Dynamic panel data models
4.1. Inconsistency of LS estimators
4.2. The Anderson-Hsiao approach
4.3. The Arellano-Bond approach
4.4. Exogenous regressors
4.5. Autocorrelation and specification tests
4.6. GMM estimation and parameter restrictions
Classes will use the software STATA 10. The same software will be used in the applications of
the 2nd and 3rd part.
References
Anderson, T.W. and C. Hsiao (1982), “Formulation and Estimation of Dynamic Models Using
Panel Data”, Journal of Econometrics, 18, 67-82.
Arellano, M. and S. R. Bond (1991), “Some Specification Tests for Panel Data: Monte Carlo
Evidence and an Application to Employment Equations”, Review of Economic Studies, 58,
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277-298.
Baltagi, B. (2001), Econometric Analysis of Panel Data, Wiley, 2nd edition.
Blundell, R. and S.R. Bond (1998), “Initial Conditions and Moment Restrictions in Dynamic Panel
Data Models”, Journal of Econometrics, 87, 115-144.
Greene, W. (2000), Econometric Analysis, Prentice Hall, 4th edition.
Hahn, J. and G. Kuersteiner (2002), “Asymptotically Unbiased Inference for a Dynamic Panel
Model with Fixed Effects When Both N and T are Large”, Econometrica, 70, 1639-1659.
Kiviet, J.F. (1995), “On Bias, Inconsistency, and Efficiency in Various Estimators of Dynamic
Panel Data Models”, Journal of Econometrics, 68, 53-78.
Manera, M. and M. Galeotti (2005), Microeconometria. Metodi e Applicazioni, Carocci.
Nickell, S. (1981), “Biases in Dynamic Models with Fixed Effects”, Econometrica, 49, 1399-1416.
2nd Part
Qualitative and Limited Dependent Variables
1. Models for qualitative dependent variables: binary choices
1.1. Linear probability model
1.2. Logit and Probit models: economic and statistical underpinnings; ML estimation;
interpretation of coefficients and marginal effects
1.3. Goodness of fit and prediction
1.4. Logit and Probit models for panel data
2. Models for qualitative dependent variables: multiple choices
2.1. Multinomial and conditional Logit models
2.2. IIA assumption
2.3. Nested Logit models
2.4. Models for ordered choices
3. Models for quantitative, limited dependent variables
3.1. Truncation and censoring
3.2. Tobit models and ML estimation
3.3. “Corrected” LS
3.4. Models with stochastic thresholds
References
Amemiya, T. (1981), “Qualitative Response Models: a Survey”, Journal of Economic Literature,
19, 483-536.
Baltagi, B. (2001), Econometric Analysis of Panel Data, Wiley, 2nd edition.
Chamberlain, G. (1980), “Analysis of Covariance with Qualitative Data”, Review of Economic
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Studies, 47, 225-238.
Greene, W. (2000), Econometric Analysis, Prentice Hall, 4th edition.
Hayashi, F. (2000), Econometrics, Princeton University Press.
Lee, M.J. (2002), Panel Data Econometrics: Methods-of-Moments and Limited Dependent
Variables, Academic Press.
Maddala, G.S. (1983), Limited Dependent and Qualitative Variables in Econometrics, Cambridge
University Press.
Manera, M. and M. Galeotti (2005), Microeconometria. Metodi e Applicazioni, Carocci.
Peracchi, F. (2001), Econometrics, Wiley.
Robinson, P.M. (1982), “On the Asymptotic Properties of Estimators of Models Containing
Limited Dependent Variables, Econometrica, 50, 27-41.
Tobin, J. (1958), “Estimation of Relationships for Limited Dependent Variables”, Econometrica,
26, 24-36.
Verbeek, M. (2000), A Guide to Modern Econometrics, Wiley.
Wooldridge, J.M. (2002), Econometric Analysis of Cross Section and Panel Data, The MIT Press.
3rd Part
Energy & Environmental Economic Modelling
1. Environment, growth and population: the Environmental Kuznets Curve hypothesis
2. Household energy demand: a discrete choice approach
3. The relationship between oil and gasoline prices: country differences and asymmetries
4. Innovation and Diffusion in Energy Technologies
References
Adeyemi, O.I. and L.C. Hunt (2007), “Modeling OECD Industrial Energy Demand: Asymmetric
Price Responses and Energy-saving Technical Change”, Energy Economics, 29, 693-709.
Balestra, P. and M.Nerlove (1966), “Pooling Cross Section and Time Series Data in the
Estimation of a Dynamic Model: The Demand for Natural Gas”, Econometrica, 34, 585-612.
Berndt, E.R., C.J. Morrison and G.C.Watkins (1981), “Dynamic Models of Energy Demand: An
Assessment and Comparison”, in E.R. Berndt and B.C. Field (eds.), Modeling and
Measuring Natural Resource Substitution, MIT Press, 259-289.
Galeotti, M., A. Lanza and M. Manera (2009), “On the Robustness of the Robustness Checks on
the Environmental Kuznets Curve”, Environmental and Resource Economics, 42, 551-574.
Galeotti, M., A. Lanza and F. Pauli (2006), “Reassessing the Environmental Kuznets Curve for
CO2 Emissions: a Robustness Exercise”, Ecological Economics, 57, 152-163.
Galeotti, M., A. Lanza and M.C.L. Piccoli (2010), “The Demographic Transition and the Ecological
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Transition: Enriching the Environmental Kuznets Curve Hypothesis”, mimeo.
Griffin, J.M. (1991), “Methodological Advances in Energy Modelling: 1970-1990”, Energy Journal,
14, 111-124.
Griffin, J. (1985), “OPEC Behavior: A Test of Alternative Hypotheses”, American Economic
Review, 75, 954-963.
Pindyck, R.S. (1979), “Interfuel Substitution and the Industrial Demand for Energy: An
International Comparison”, Review of Economics and Statistics, 61, 259-268.
Pireddu, G. and S.D’Ascenzo (1996), “I modelli di scelta aleatoria: Metodologia e applicazione al
caso della scelta del sistema di riscaldamento”, Economia delle fonti di energia e
dell’ambiente, 39, 139-177.
Popp D. (2002), “Induced Innovation and Energy Prices”, American Economic Review, 92, 160180.
Ramcharran, H. (2002), “Oil Production Responses to Price Changes: An Empirical Application
of the Competitive Model to OPEC and Non-OPEC Countries”, Energy Economics, 24, 97106.
Stevens, P. (2000), “The Economics of Energy 1”, Journal of Energy Literature, 6, 3-31.
Stevens, P. (2001), “The Economics of Energy 2”, Journal of Energy Literature, 7, 3-45.
Vaage, K. (2000), “Heating Technology and Energy Use: A Discrete Continuous Choice
Approach to Norwegian Household Energy Demand”, Energy Economics, 22, 649-666.
Verdolini, E. and M. Galeotti (2011), “At Home and Abroad: An Empirical Analysis of Innovation
and Diffusion in Energy Technologies”, Journal of Environmental Economics and
Management, 61, 119–134.
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Course Timetable
Sunday, 8 September 2013
- Hotel President, h.18.00: Welcome meeting
Monday, 9 September 2013
- Camera di Commercio, h. 9.00-9.15: Presentation of the course
- Camera di Commercio, h. 9.15-13.00: Stationary Panel Data Models (lecture)
- Camera di Commercio, h. 14.30-18.00: Stationary Panel data Models (lecture and class)
Tuesday, 10 September 2013
- Camera di Commercio, h. 9.00-13.00: Stationary Panel Data Models (lecture)
- Camera di Commercio, h. 14.30-18.00: Stationary Panel Data Models (lecture and class)
Wednesday, 11 September 2013
- Camera di Commercio, h. 9.00-10.30: Qualitative and Limited Dependent Variables (lecture)
- Banca d’Italia, h. 11.00-13.00: Seminar (*)
- Camera di Commercio, h.14.30-18.00: Qualitative and Limited Dependent Variables (lecture)
Thursday, 12 September 2013
- Camera di Commercio, h. 9.00-13.00: Qualitative and Limited Dependent Variables (lecture and
class)
- Camera di Commercio, h.14.30-18.00: Qualitative and Limited Dependent Variables (lecture
and class)
Friday, 13 September 2013
- Camera di Commercio, h. 9.00-13.00: Qualitative and Limited Dependent Variables (lecture and
class)
- Camera di Commercio, h.14.30-18.00: Energy & Environmental Economic Modelling (lecture)
Saturday, 14 September 2013
- Camera di Commercio, h. 9.00-12.00: Energy & Environmental Economic Modelling (lecture
and class)
- Camera di Commercio, h. 12.00-12.30: Diploma awards delivery and final comments
(*) TBA
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