Topics will be announced when offered.
Topics will be announced when offered.
Topics will be announced when offered.
Topics will be announced when offered.
Topics will be announced when offered.
Topics will be announced when offered.
Topics will be announced when offered.
Topics will be announced when offered.
This course will examine the role played by institutions and political economy considerations in determining overall economic performance. The course aims to describe the role and evolution of institutions in economic growth, to understand basic models of politics, and to provide an introduction to the dynamic effects of fiscal and monetary policy. By the end of the course, students should be able to understand the the role of institutional failure, models of governance and mis-governance, optimal fiscal policy, and the concepts of reputation, credibility, and time inconsistency.
Introduction to Turkish economy and Turkish economic institutions: Recent history of the economy; Inward vs outward strategies, political institutions and long-term growth performance; Short-run economic fluctuations, inflation and unemployment; Monetary, fiscal and ex change rate policies; Trade and international competitiveness of the industry; Capital flows, foreign direct investment and privatization; Impact of the local and global financial crises on the economy.
Macroeconomic analysis of daily developments in the Turkish economy; Analysis of key concepts and data; How to use macroeconomic identities in policy analysis; The analysis of Türkiye?s growth and inflation record; Measures of fiscal position, fiscal adjustment and debt sustainability; The balance sheet of the Central Bank; How Turkish Central Bank conducts monetary policy; Balance of payments developments; Analyzing vulnerabilities and sovereign risk.
Integration of the knowledge from different areas of the economics curriculum: microeconomics, macroeconomics, econometrics by applying concepts and frameworks to real life cases to formulate and implement creative and effective solutions to economic challenges; teamwork and presentations.
To facilitate a swift transition from undergraduate to graduate training, the mathematical foundation that all students should have will be reviewed. Topics include: mathematical statements and proofs; functions; sequences and limits; continuity; differentiation; metric spaces; integration.
Covers selected topics in mathematics that are frequently used in economic theory and its applications. Topics include: introduction to optimization theory (existence of a solution, alternative characterizations of compactness, Weirestrass Theorem, convexity); convex sets, concave and quasi-concave functions; characterization of a solution, Lagrange and Kuhn-Tucker approaches; parametric continuity, correspondences and maximum theorem; parametric monotonicity, lattices, supermodularity; fixed point theorems.
Consumer theory; production theory; general equilibrium and welfare.
Choice under uncertainty; game theory; mechanism design; principal-agent models.
The course includes topics such as the game theory under perfect information, game theory under imperfect information, matching and mechanism design.
Long-term economic growth; overlapping generations models; consumption, saving, and investment; real interest rates and asset prices; money and inflation.
Classical and Keynesian theories of cyclical fluctuations; real business cycle theory; determination of employment and real wages; credit markets and financial stability; stabilization policy.
The course includes topics such as the business cycle theory, dynamic stochastic general equilibrium models, models of unemployment with search, market efficiency and macroeconomic performance, and theories of long-run growth.
Review of probability and statistics: random variables, univariate and joint probability distributions, expectations; bivariate normal; sampling distributions; introduction to asymptotic theory; estimation; inference. Linear regression: conditional expectation function; multiple regression; classical regression model, inference and applications.
Departures from the standard assumptions: specification tests; a first look at time series; generalised regression; nonlinear regression; simultaneous equations, identification, instrumental variables. Extensions and applications: ML, GMM, VAR, GARCH, panel data.