JOURNAL OF ECONOMIC MODELING RESEARCH
Year:2012 | Volume:3 | Issue:9|Papers Count:7

The ultimate goals of the monetary policy are price stability and the output growth. Monetary policy instruments are interest rate and the growth rate of monetary base. One of the well-known rules in conducting monetary policy is Taylor rule, through which, central banks change the interest rate while taking into account the output and inflation distortions. There are two problems with applying Taylor rule in Iran: First, the weak micro-foundation of the rule and second, according to this rule specially in the short run, instead of interest rate the policy variable is the growth rate of the monetary base. This research extends Taylor rule by explaining micro-foundation of the rule. So, using Generalized Method of Moments (GMM), we investigated the consistency of the Iranian central bank’s reaction function with extended Taylor rule in the period 1979- 2008. The empirical results show that although monetary authorities react appropriately with respect to output distortion, but their reaction is not appropriate with respect to inflation distortion.

In recent years, financial economists have increasingly recognized the interaction between market structure and capital structure or financial decisions of the firms.This research analyzes the relationship between market structure (power) and the capital structure (leverage ratio) of listed companies in Tehran Stock Exchange (TSE) based on static and dynamic approach. In this research we study a balanced panel dataset of 101 firm-year observations from 2006 to2010 and test significant relationship for testing hypothesis.First we use pooled regression to determinant the relationship between capital structure, market structure (Tobin's Q) and five control variables including profitability, size, collateral value of assets, growth rate of assets and uniqueness of assets. After employing chow and hausman test, we selected fixed effect panel data model. Also we employed GMM method to have more efficient result and also to cope with the unobservable firm-specific characteristics and endogeneity problems.Our results suggest that the relationship between leverage and market structure is non-linear (cubic) due to the complex interaction of market conditions, agency problems and bankruptcy costs. The study finds a negative relationship between capital structure and profitability and also positive relation between capital structure and the size. So, profitable companies tend to use internal financing such as retained earnings and issuing new shares instead of debt financing. Also big companies prefer to use more leverage due to desirable conditions for getting loans. Our evidence shows that Iranian listed companies are generally more subject to agency cost theory (limited liability effect) and tax shield theory. Finally, the system-GMM results reveal that managers of Iranian firms tend to adjust dynamically their leverage ratios over time.

In this paper a new model for optimal investment in advanced manufacturing machines is proposed, using fuzzy linear programming. In the first step decision-makers determine the strategic objectives of the company and their minimum acceptable achievement levels, using fuzzy numbers. Thereafter, feasible alternatives and their degree of influence to the achievement of each objective are concluded in the form of linguistic variables. To construct the model, the degree of influence of each alternative in the achievement of the objectives are considered as technological coefficients, and the minimum level of acceptance of objectives are considered as constraints (right hand side variables). Furthermore, the mutually exclusive alternatives, the interaction between machines and the constraint of limited investment of budget are included in the model. The aim of the model is to determine the number of machines that needs to be purchased in order to maximize the present value of investment. The calculation of net present value is executed based on discount cash flow, inflation rate, interest rate, revenue and costs of each machine on a fuzzy environment. Finally by presenting an empirical illustration, the performance of this model is clarified.

This paper investigates the relationship between real exchange rate uncertainty and stock price index in Tehran stock exchange for the period of 1995-2009 by using monthly data and applying Bivariate Generalized Autoregressive Conditional Heteroskedasticity model (Bivariate GARCH). The results show that there is a negative and significant relationship between real exchange rate uncertainty and stock price index. However, the relationship between stock price uncertainty and real exchange rate is insignificant. Therefore, our results recommend that the policies which cause more volatility in the exchange market and also more volatility in the real exchange rate should be avoided to ensure the sustainable growth of the stock market and its price index.

Parties and candidates in the election campaign try to raise the community to vote for them by offering a variety of social policies. However, the public health expenditures have been raised among the candidates as one of the most important tools to attract votes. Thus, this study uses panel data to investigate whether the components of electoral cycle have affected the growth of public health expenditures in both developed and developing countries over the period of 1994-2010. Using the related tests, two methods of static panel (random effects) and dynamic panel estimation were selected. According to the results, the presence of electoral cycles could not be rejected in both types of countries. Based on these results, politicians in every country increase the public health expenditures before the election in hopes of gaining a greater share of people's votes.

In this study we compare a set of Markov Regime-Switching GARCH models in terms of their ability to forecast the Tehran stock market volatility at different time intervals. SW-GARCH models have been used to avoid the excessive persistence that usually found in GARCH models. In SW-GARCH models all parameters are allowed to switch between a low or high volatility regimes. Both Gaussian and fat-tailed conditional distributions are assumed for the residuals, and the degrees of freedom can also be state-dependent to capture possible time-varying kurtosis. Using stationary bootstrap and re-sampling, the forecasting performances of the competing models are evaluated by statistical loss functions. The empirical analysis demonstrates that SW-GARCH models outperform all standard GARCH models in forecasting volatility. Also, the SW-GARCH model with the t distribution for errors has the best performance in fitting a model and estimation.

A standard assumption in the empirical literature is that exchange rate pass-through is both linear and symmetric. This implies that size (large-versus-small exchange rate changes) and direction (currency appreciations-versus-depreciations) have similar effects. In this paper these assumptions have investigated for Iran's export prices. So, this paper examines the asymmetric exchange rate pass-through to the monthly import price index in Iran during 1997:1–2010:9. Therefore positive and negative exchange rate shocks have been separated using Mork Criteria and large and small exchange rate changes by determining a threshold. The results show that the response of export prices to currency appreciation and depreciation is asymmetric. So, the negative exchange rate shocks have a greater effect on the export prices than the positive exchange rate shocks. According to our estimation results, there is a threshold at 1.3% of monthly changes in exchange rate of Iran and also export prices react asymmetrically to exchange rate at around this threshold. If both direction and size effects are considered, we find that export prices respond asymmetrically to large and small appreciations and depreciations.