Damba Lkhagvasuren
Work in Progress
Wage Dynamics and Industrial Mobility (joint with Stephane Auray and Antoine Terracol)Unemployment Benefits in a Multi-Sector Economy (joint with David Fuller)On Directedness of Job Search with Search Tenure (joint with Marianna Kudlyak)
Research PapersThe finite state Markov-Chain approximation method developed by Tauchen (1986) and Tauchen and Hussey (1991) is widely used in economics, finance and econometrics in solving for functional equations where state variables follow an autoregressive process. For highly persistent processes, the method requires a large number of discrete values for the state variables to produce close approximations which leads to an undesirable reduction in computational speed, especially in a multidimensional case. This paper proposes an alternative method of discretizing vector autoregressions. This method can be treated as an extension of Rouwenhorst's (1995) method which, according to our experiments, outperforms the existing methods in the scalar case for highly persistent processes. The new method works well as an approximation that is much more robust to the number of discrete values for a wide range of the parameter space.
Considerable
labor mobility exists within the U.S., enough that, if migration
arbitrages unemployment differences, one might expect very low
cross-state unemployment differences. However, local unemployment data
reveal that there are large cross-state unemployment differences. A
dynamic general equilibrium model of worker migration and job search is
introduced to account for these data features. The interaction between
location-specific individual productivity and firm-worker trading
frictions is important for understanding local unemployment. In the
model, labor mobility and aggregate unemployment are negatively related,
a prediction that is in stark contrast to the standard theory of
sectoral reallocation, but consistent with the U.S. data.
The Cyclicality of Search Intensity in a Competitive Search Model
(joint with Paul Gomme)
Reasonably calibrated
versions of the Diamond-Mortensen-Pissarides search and matching model of
unemployment underpredict, by a wide margin, the volatility
of vacancies, unemployment, and
the vacancies-unemployment ratio - variables at the heart of this model.
These
shortcomings motivate two modifications to the
Diamond-Mortensen-Pissarides
model. First, wages are determined via competitive search (wage posting
by
firms along with directed search on the part of workers) rather than the
usual
Nash bargaining. This change is motivated by the fact that most
unemployment variation
in the U.S. is due to non-college educated individuals, and that wages
of
newly-hired non-college educated workers are predominantly set by wage
posting. Second, workers are permitted to take direct action to affect
the outcome of
their labor market search through search effort. With these
modifications in
place, the benchmark model captures 70% of the standard deviation of
unemployment and the vacancies-unemployment ratio, and almost 80% of the
volatility of vacancies. A recalibration of the model that targets the
variability of the vacancies-unemployment ratio results in reasonable
parameters, and can account for almost all of the cyclical variability
in
unemployment and vacancies.
A Moment-Matching Method for Approximating Vector Autoregressive
Processes by Finite-State Markov Chains
(joint with Nikolay Gospodinov)
This paper proposes a moment-matching method for approximating vector autoregressions by finite-state Markov chains. The Markov chain is constructed by targeting the conditional moments of the underlying continuous process. The proposed method is more robust to the number of discrete values and tends to outperform the existing methods for approximating multivariate processes over a wide range of the parameter space, especially for highly persistent vector autoregressions with roots near the unit circle.
Key Moments in the Rouwenhorst Method (a short note)
It is well know that in approximating highly persistent AR(1) shocks by a finite-state Markov chain, the method of Rouwenhorst
(1995) outperforms other existing methods along key lower-order moments.
Although lower order moments are sufficient to evaluate the
existing few methods, it is important to understand how the method
performs along higher-order moments of the underlying process. This note
calculates higher-order moments of the process generated by the
Rouwenhorst method. The results
can be useful in approximating autoregressive processes whose
higher-order moments are different than those of the normal
distribution.
A Dynamic Perspective on Why the More Educated Move More Often
Motivated by large educational
differences in geographic mobility, this paper extends a Roy model of locational
choice to a dynamic stochastic setting where mobility and wages are jointly
influenced by moving costs and a persistent, idiosyncratic location-match
shock. The model accounts for key
features of labor mobility and wages, including new evidence on wage differences
between migrant and non-migrant workers of different age and educational groups. According to the model, the location-match shock
is larger for more educated workers and accounts for the bulk of educational
differences in mobility. In the absence of the persistent location-match shock,
there is no meaningful relationship between mobility and moving costs.
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