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Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General to Specific’ he role of ceteris paribus in a theory model versus n an empirical model
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Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Jan 03, 2016

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Lisa Shelton
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Page 1: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Taking the theory to the data:A proposal

Romer: Advanced Macroeconomics, Chapter 9:Inflation and Monetary Policy

‘Specific to General’ versus ‘General to Specific’

The role of ceteris paribus in a theory model versusin an empirical model

Page 2: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

What causes inflation?

Many potential causes:Shocks shifting the AD curve to the right or the AS curve to the left leads to higher prices

Page 3: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Inflation and money growth

Endogenous, exogenous variables? Ceteris paribus assumptions?

Equlilibrium in the money market:

Inverting the equilibrium money relation:

Deviations from long-run benchmark levels:

Page 4: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Deviations from a long-run money demand relation

Excess money measured as: m-p-y-13(Rm-Rb)

Page 5: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Examples of empirical questions

Page 6: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Time dependence of macro data

• Stationary variables with a short time dependence, i.e. a low degree of time persistence, transitory effcts

• Nonstationary variables with long time dependence, i.e. high degree of time persistence, permanent effects.

Distinguish between:

Page 7: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

What is the long run?

Unit root as a local approximation of persistent behavior !

Page 8: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.
Page 9: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Stationary and nonstationary movements in the data

• stationary movements have a short memory (transitory components)

• nonstationary movements have a long memory (persistent components)

• cointegration between nonstationary variables eliminate the nonstationarity. A cointegration relation can often be interpreted as a long-run economic relation

• distinguish between short-run and long-run structures in the data

Page 10: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

How do we measure long-term movements in the data?

• Deterministic trends (usually linear)

• Stochastic trends (persistent movements in the data

• A combination of the two

Page 11: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

A stochastic formulation

What is the meaning of a stochastic trend and a stochastic long cycle?

Page 12: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Illustrative example of how to measure a stochastic trend

Page 13: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Measuring a stochastic trend

Page 14: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

The stochastic trend in inflation

Page 15: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

• The increments of a deterministic trend are constant over time• The increments of a stochastic trend are random over time

• First and second order stochastic trends

Page 16: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

1970 1975 1980 1985 1990 1995 2000 2005

0.0

0.5

1.0

1.5 Lp

1970 1975 1980 1985 1990 1995 2000 2005

0.000

0.025

0.050Dp

1970 1975 1980 1985 1990 1995 2000 2005

0.02

0.04 DpMA

Page 17: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.
Page 18: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Are prices I(1) or I(2)?

Page 19: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

The I(2) Scenario

Defining autonomous shocks • Theoretically• Empirically

• Shocks shifting the AD curve• Shocks shifting the AS curve

Page 20: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Conditions for long-run price homogeneity

Page 21: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Assuming price homogeneity

Page 22: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.
Page 23: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.
Page 24: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

A theory consistent scenario

Inflation I(1) ?

Page 25: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Why does nonstationarity matter for the statistical modelling?

• Standard statistical inference is based on stationarity.

• Some new inferences is needed, but by transforming the data into differences and cointegration relations stationarity is recovered.

• Pulling and pushing forces

Page 26: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

Why does nonstationarity matter for the economic modelling?

• Most economic models are developed for a stationary world

• The role of the ceteris paribus assumption

• The role of expectations– Model based rational expectations

– Imperfect knowledge expectations

Page 27: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

I had the great good fortune in the 1960s to initiate the profession’s work on plausible microfoundations for macroeconomic modeling taking into account the knowledge and the information that the micro actors could reasonably be supposed to have – truly a revolutionary movement. Unfortunately, the rational expectations models appearing in the 1970s sidestepped the problem of expectations formation under uncertainty by blithely supposing that the model’s actors (tellingly dubbed “agents”) knew the “correct” model and the correct model was the analyst’s model – whatever that model might be that day. The stampede toward “rational expectations,” referred to as a “revolution” though it was only a generalization of the neoclassical idea of equilibrium, derailed the movement I initiated. In the end, this way of modeling has not illuminated how the world economy works. Happily for me and I believe for the profession of economics, this book gives signs of bringing us back on track – on a road toward an economics possessing a genuine microfoundation and at the same time a capacity to illuminate some of the many aspects of the modern economy that the rational expectations approach cannot by its nature explain.

Page 28: Taking the theory to the data: A proposal Romer: Advanced Macroeconomics, Chapter 9: Inflation and Monetary Policy ‘Specific to General’ versus ‘General.

The I(1) scenario