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General information |
Course unit name: Business Econometrics
Course unit code: 363664
Academic year: 2025-2026
Coordinator: Samuel Calonge Ramirez
Department: Department of Econometrics, Statistics and Applied Economics
Credits: 6
Single program: S
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Estimated learning time |
Total number of hours 150 |
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Face-to-face and/or online activities |
60 |
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- Lecture with practical component |
Face-to-face |
30 |
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(Carried out every week during the first session, under the lecturer supervision. It consists of lectures and problem-solving sessions to introduce and explain the course content.) |
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- IT-based class |
Face-to-face |
30 |
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(Carried out every week during the second session, under the lecturer supervision and in the computer room. Students must complete the nine practical activities established in the syllabus.) |
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Supervised project |
40 |
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(Focused on completing the set problems, exercises and practical activities.) |
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Independent learning |
50 |
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(Independent learning is focused on knowing how to solve and interpret the regression model using software.) |
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Recommendations |
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It is imperative that students have the proficiency in algebra and calculus acquired through successful completion of the subjects Mathematics I and II.
Further recommendations Students who take this course must demonstrate a working knowledge of Excel-type spreadsheets, as well as a reasonable level of computer skills. Requisites 363645 - Mathematics I (Recommended) 363646 - Mathematics II (Recommended) 363647 - Statistics I (Recommended) 363648 - Statistics II (Recommended) 363649 - Introduction to Econ (Recommended) 363650 - Microeconomics (Recommended) 363651 - Macroeconomics (Recommended) |
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Competences / Learning outcomes to be gained during study |
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To be able to use ICT in professional practice. |
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To use basic quantitative methods and instruments to obtain and analyse company information and its socioeconomic environment, in accordance with the characteristics of the available information. |
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Learning objectives |
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Referring to knowledge — Be introduced to econometric methods.
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Teaching blocks |
1. The multiple linear regression model (MLRM): specification and statistical inference
1.1. MLRM analysis: statistical properties
a) Formulation and basic hypotheses
b) Estimation
c) Measures of goodness of fit
d) Variance analysis
e) Interpretation of results
1.2. Statistical hypothesis testing. Validation of MLRM
a) Hypothesis testing with parameters
b) Point and interval forecasting. Predictive capacity measures
c) Restricted estimation
d) Structural change, linearity and normality testing
1.3. Processing sampling errors in MRLM: atypical data (outliers) and multicollinearity
a) Outliers and influential observations
b) Main tests and indicators for atypical data
c) Multicollinearity: definition, degrees and consequences in the estimation of ordinary least squares (OLS)
d) Detection, assessment and solution of multicollinearity
2. Extension and expansion of MLRM
2.1. Processing qualitative information in the context of MLRM
a) Regression model specification with exogenous dummy variables
b) Ordinary least squares (OLS) estimation
c) Interpretation of parameters
d) Using dummy variables in structural change tests
2.2. MLRM under heteroscedasticity
a) Non-spherical disturbance: consequences on OLS estimation
b) Generalized least squares (GLS)
c) Tests for heteroscedasticity
2.3. Omissions, errors and endogeneity in MLRM explicative variables
a) Instrumental variables estimator (IV)
b) Two-stage least squares estimator (2SLS)
c) Contrasts in endogeneity
2.4. Logit model of binary responses
a) Specification of the logit model
b) Maximum-likelihood estimation
c) Interpretation of estimations
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Teaching methods and general organization |
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The subject Business Econometrics belongs to the wider field of quantitative methods in economics and therefore requires a considerable amount of empirical work. Real statistical data are used for study, and students must be familiar with the principal official sources of statistics and know how to apply the appropriate econometric and computing tools to the resolution of econometric models.
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Official assessment of learning outcomes |
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Continuous assessment
Examination-based assessment — Students who wish to opt for this method of assessment must follow the guidelines established by the Faculty of Economics and Business. For further information, consult the Regulations for the assessment and marking of learning outcomes (especially point 6.4), which can be found in the Regulations section of the Faculty of Economics and Business website.
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Reading and study resources |
Check availability in Cercabib
Book
| This book gathers all the elements related to the practical sessions that will be carried out throughout the course in the computer classrooms. Complementary material is available: examples of mathematical functions and statistics from Excel (practical session 1), database for the practical sessions and the MicroEconometria program, accessible from the LiberWeb of UB Publications. |
| This book comprises a collection of multiple-choice exercises, classified by topic, and includes the workings and justification of each solution. |
ARCARONS BULLICH, Jordi; CALONGE RAMÍREZ, Samuel. Microeconometría : introducción y aplicaciones con software econométrico para Excel. Madrid : Delta, 2008
| This book contains the main theoretical formulations required for the subject. It also contains chapters on intermediate and advanced econometrics, which are useful for subsequent postgraduate and doctoral study in areas related to econometric methods. It includes the program MicroEconometria, an econometrics application that works within the Excel environment. |
WOOLDRIDGE, Jeffrey M. Introducción a la econometría : un enfoque moderno. 4ª ed. México, DF : Cengage Learning, 2010
| This is intended as complementary reading and takes a more theoretical approach to the subject content. Students will find it a useful reference for solving specific queries and for finding out more about specific, complex topics. |