EFFICIENCY AND PRODUCTIVITY ANALYSIS Syllabus

 

 

Syllabus

1) Principles of national and sectorial accounting, data and variables definitions

2) Sectorial production analysis: static and dynamic input-output tables. Sectorial productivity

and rates of growth

3) Microanalysis: the firm’s problem and the stochastic frontiers. Parametric and

semiparametric analysis. Adjustment models.

4) Efficiency analysis: cost function, profit function, revenue function

5) Output efficiency

6) Input efficiency

7) Flexible functional forms

8) Estimations methods for stochastic frontiers

9) Productivity analysis (macro and micro): production function, total factor productivity,

growth and ICT externalities. Theory and estimation.

10) Efficiency and productivity analysis: an application to the banking sector

 

AIMS of the course:

This course has the target of providing the students with the modern techniques of measuring

quantitatively advanced topics in economic statistics. In particular, our focus will be on three main

interrelated directions: 1) the analysis of production and efficiency, specifically in the private but

also in the public sectors, 2) economic dynamics of sectorial systems founded on micro data, 3) growth, ICT and technology in the modern economy.

This course uses statistical methods, both stochastic and deterministic, to analyze topics such as productivity, efficiency and growth at micro, sectorial, and for coherence at macro level. We first take into exam data from firms that will be useful for the mentioned three-level study, then, as regards the efficiency analysis of productive units, such data will be employed in order to evaluate mergers and acquisitions of plants and firms and management of productive factors. Efficiency will be evaluated from the sides of costs, profits and revenues. As for the sectorial analysis, static and dynamic models will be considered to allow for forecasts and simulations in each sector for variables like production, labour, capital, raw materials, prices and capital gains. As a consequence, an aggregate analysis on the production, growth and prices will follow. We also deal with ICT and technical progress in the production process considering how and if the associated externalities are effective. We will use the following techniques for data analysis: accounting rules for the database, panel data econometrics, (possibly) time series analysis for systems of equations, methods for differential equation systems. Topics on private and also public sectors will contribute to explain the relationship between economic structure and the actual crisis. Specifically, lectures also include the examinations of cases study concerning the efficiency and productivity analysis on the recent patterns of the banking sector in the international context.

Two main parts characterize the course. The first part considers the sectorial productivity analysis, the second part the efficiency and productivity analysis of firms (micro level).

 

Reference

Books:

Alvaro G. (2000), "Contabilità nazionale e statistica economica", terza edizione, Cacucci editore, Bari, terza edizione. (pp. 31 – 71, pp. 145 – 271, pp. 652 - 745)

Battese Tim, D.S. Rao, G. Coelli (1997), “An introduction to efficiency and productivity analysis”, Kluwer academic publisher.

Gandolfo (2009), Economic Dynamics, Springer. (pp. 237-254; 254-264, consigliabile; pp. 265-268; pp. 268-278, consigliabile; pp. 293-298; pp.337-341, consigliabile;)

Giovannini, E., (2006), Le statistiche economiche, Il Mulino, Bologna.

Giusti F Vitali O. (1999), Statistica Economica, Cacucci, Bari.

Greene W., (2013), Econometric Analysis, McMillan. (pp.198 -201, pp.287 -301, pp.40 -347,

pp.824 -825, pp.864 -865, pp.903 -904, pp.909 -913)

Hamilton J., (1994), Time series analysis, Princeton University Press

Siesto V. (2003), La contabilità nazionale italiana: il sistema dei conti del 2000, Il Mulino, Bologna.

Varian, H., R., (1992) Microeconomic Analysis, Third Edition, Norton.

 

Articles

Berger A., Leusner J., Mingo J., (1997), “The efficiency of bank branches”, Journal of

Monetary Economics, n° 1, n. 40, pp. 141-162.

Berger A, Mester, L.J., (2001), “Explaining the dramatic changes in performance of US banks:

technological change, deregulation, and dynamic changes in competition, WP n° 01-6, The Wharton Financial Institutions Center, University of Pennsylvania.

Rolf F., Grosskopf, S., Lovell, C.A., Yaisawarng, S., (1993), “Derivation of Shadow Prices for

Undesirable Outputs: A Distance Function Approach”, The Review of Economics and Statistics Vol. 75, No. 2, pp. 374-380

Gallant, R., (1981), “On the bias of flexible functional forms and an essentially unbiased form”,

Journal of Econometrics, n. 15, pp. 211-245.

Gallant, R., (1982), “Unbiased determination of production technologies”, Journal of Econometrics, n. 20, pp. 285-323.

White, A., 1980. “Using Least squares to approximate unknown regression functions”.

Maggi B., Guida M., (2011), Modelling non-performing loans probability in the commercial

banking system: efficiency and effectiveness related to credit risk in Italy, Empirical Economics, n. 2, pp 269-291

Pastor, J. M., Serrano L., (2005), "Efficiency, endogenous and exogenous credit risk in the banking systems of the Euro area," Applied Financial Economics, vol. 15(9), pp. 631-649.

Petretto A. e Pisauro G. (1994), “Struttura produttiva dell’amministrazione delle imposte dirette e costi di enforcement”, Politica Economica, n.1. pp 3-41.

Shephard, R. W., 1970. Theory of cost and production function. Princeton University Press,

Princeton, NJ.

Simper, R., 1999. Economies of scale in the Italian saving banking industry. Applied Financial

Economics 9, 11—19.

Xavier Sala-i-Martin (1990), Lecture notes on economic growth (I and II): introduction to the

literature and neoclassical models, NBER WORKING PAPERS SERIES N. 3563, 3564.

 

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