DSGE model

Chapter 1 Introduction

1.1 Oil and Macroeconomic

The macroeconomic effects of oil include oil price and oil consumption. Oil can usually be used for several applications. Petrolasconsumption goodscan be used as fuel and oilas production goods can be usedas raw materials forpetrochemical industries.Oil price fluctuations are usually treated as a exogenous disturbances where are unrelated to any economic fundamentals (Peersman and Stevens, 2012). Sudden and protracted oil price increases are generally accompanied by economics contractions and high inflation (Hamilton, 1983).Researchers and policymakers are often interesting in the impacts of oil price shocks on output and the effects related to the endogenous policy responses of monetary policy and tax policy.Changes in oil prices have a direct impact on the price level of the economy, they affect consumption decisions, and also influence the cost structure of firms and through this channel have a second-rounded effect on domestic prices. Wage and price indexation can propagate the effects of oil-price shocks on inflation and output. Recent empirical studies have revealed that the effects of oil shocks became muted after the mid-1980s. These studies obtained similar conclusions: the typical response to an oil shock is a decrease in the real GDF growth rate and real wage, leading to inflation and so on. (Hongzhi, 2010 ).

In general, oil tax would induce the rising of oil price and inflation. The contractionary effect of oil price shock can be due to the endogenous tightening of the monetary policy.However,oil tax would induceoil consumption and carbon dioxide emissions, so it is important for energy saving and carbon reduction.

1.2 DSGE model

The function of a model of analysis and simulation for economy is twofold : to serve as a tool for policy analysis and to serve as a tool for forecasting key macroeconomic variables (Medina an Soto, 2011). Not only the first-round effects of different shocks can be understood but also second-round

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effects can be considered.In the past, general economic forecasting models of business cycle are in the form ofsimultaneous-equations structural models. The linear structures of these models are as the same as the Vector Autoregressive model. So the Vector Autoregressive model is used to be as the main analytic tool for economic forecasting. However, there are some of the following problems:

first the correct number of variables needs to be excluded, and second the projected future values are required for the exogenous variables in the system.

One of advantages of the model is that the structural interpretation of the disadvantage of the Luca’s critique on the traditional analysis of policy effects (Medina and Soto,2006)( Liao and Teng, 2008). Lucas(1976) indicated that estimated functional forms obtained for macroeconomic models in the Keynesian tradition and the Vector Autoregressive model do not correctly account for the dependence of private agent’s behavior on anticipated government policy rules. The famous “Lucas critique”pointed out:

"Given that the structure of an econometric model consists of optimal decision rules of economic agents, and that optimal decision rules vary systematically with changes in the structure of series relevant to the decision maker, it follows that any change

in policy will systematically alter the structure of econometric models."

Relatively, DSGE models can handle both the possibilities of structural changes and the problems of nonlinearities, since DSGE models are able to identify that the actions of rational agents are not only dependent on government policy variables, but also on government policy rules (Liu and Gupta, 2007). The purpose of DSGE models is to interpret how the microeconomic principles derive aggregate economic phenomena including business cycles, economic growth, and the effects of monetary and fiscal policy. Figure 1.1 shows the typical structure of a DSGE model. DSGE models also study how the economy evolves over time and how the economy is affected by random shocks such as technological change, fluctuations in the price of oil, or macroeconomic polices. The

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decision-makers in DSGE model, often called 'agents', may include households, firms, and governments or central banks and DSGE models are constructed on the basis of assumptions about agents' preferences. There are two issues considered in DSGE models: one is that it is possible to ask whether the policies considered are Pareto optimal, another is or how well agents satisfy some other social welfare criterion derived from preferences. In recent years, the DSGE model has been the baseline framework used for theoretical analysis of monetary policy and tax policy.

Fig 1.1 The structural chart of a DSGE model

The DSGE model is the best decision of households’ utility and firms’profit in different constraints. But the original DSGE model is nonlinear so that it will be log-linearized to obtain a linearized steady state model. Then the first order Taylor’s expansion of a DSGE model will be transfer to simultaneous equations. The deviations of endogenous variables, which be obtained by solving the simultaneous equations present the fluctuations of endogenous variables. In fact, there are many uncertainties in real economic environment and these uncertainties could be presented by

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applying exogenous shocks.

The hypotheses of the RBC-DSGE model includes rationalexpectation, perfect elasticity of wage and price, and the market is clean. However, the hypotheses of the new Keynesian DSGE model includes rational expectation, nominal rigidityof wage and price, and the market is not always clean.

There are three methods for estimating the structural parameters of a DSGE model: calibration, maximum likelihood estimation and Bayesian estimation. And the log-linearized model of the DSGE model can be solved by Blanchard and Kahn method.