Taking the theory to the data: A proposal

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Taking the theory to the dataA 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
versus in an empirical model
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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
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Inflation and money growth
Equlilibrium in the money market
Inverting the equilibrium money relation
Endogenous, exogenous variables? Ceteris paribus
assumptions?
Deviations from long-run benchmark levels
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Deviations from a long-run money demand relation
Excess money measured as m-p-y-13(Rm-Rb)
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Examples of empirical questions
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Time dependence of macro data
Distinguish between

• 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.

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What is the long run?
Unit root as a local approximation of persistent
behavior !
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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

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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

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A stochastic formulation
What is the meaning of a stochastic trend and a
stochastic long cycle?
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Illustrative example of how to measure a
stochastic trend
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Measuring a stochastic trend
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The stochastic trend in inflation
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• 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

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

• Defining autonomous shocks
• Theoretically
• Empirically

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

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Conditions for long-run price homogeneity
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Assuming price homogeneity
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A theory consistent scenario
Inflation I(1) ?
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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

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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

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I had the great good fortune in the 1960s to
initiate the professions 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 models actors (tellingly dubbed
agents) knew the correct model and the
correct model was the analysts 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.
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The I(1) scenario