Three essays on regional business cycle analysis

Chung, Sungyup

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https://hdl.handle.net/2142/78356 Copy

Description

Title

Three essays on regional business cycle analysis

Author(s)

Chung, Sungyup

Issue Date

2015-04-10

Director of Research (if dissertation) or Advisor (if thesis)

Hewings, Geoffrey J.D.

Doctoral Committee Chair(s)

Hewings, Geoffrey J.D.

Committee Member(s)

• Bera, Anil K.
• McMillen, Daniel P.
• Chung, Eun Yi

Department of Study

Economics

Discipline

Economics

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Multi-level
• Regional Economy
• Business Cycle
• Dynamic Factor Model
• Markov Regime Switching
• Scale of Observation

Abstract

In this dissertation, regional business activities are analyzed under the assumption of multi-level structure regional economic system. Compared to a single-level regional economic system, a multi-level regional economic system assumes that regional economies are exposed to a common factor that affects its sub-units. In the first essay, it is found that in multi-level structure regional economy, spillovers from neighboring regions are insignificant or small compared to common factor. Adapting the conclusions from the first essay, the second essay studies how the common factor affects the transition dynamics and economic performances of regional economies. The last essay explores how temporal/spatial scale of units of regional observations affects the estimated amount of spillovers under the same data generating process. The first essay uses a multi-level dynamic factor model suggested by Bai and Wang (2012) to identify the spatio-temporal dynamics of regional business cycles, focusing on six Great Lakes states, Illinois, Indiana, Michigan, Minnesota, Ohio and Wisconsin. The identification scheme suggested by Bai and Wang (2012) enables separate identification of the shock common to the Great Lakes region and the individual shock to each region as well as an assessment of the interactions between those shocks. The multi-level approach enables us to assess the effect of a shock originating in one particular region on the other regions separately from the region common shock. In contrast, a single-level approach does not separate the region common shock from the region specific shock. By separating out the global shock from the local observations, this multi-level approach prevents the possible misunderstanding of regional interdependency induced from the comovements of regional business cycles. Since each region is exposed to the region common shock, the degree of comovement of each region’s business cycle is strong, possibly exaggerating or biasing the effect of region specific shocks. The simulation results show that incorporating the multi-level structure in a regional dynamic factor model significantly alters the regional interdependency relationship extracted from the single-level structure model. The variance decomposition shows that much of the region specific business activities can be explained by the region common shock, and the cumulative impulse response function occasionally shows different signs for the long-term response compared to the single-level structure model. The second essay is composed of two parts. The first part dates the regional business cycle phases using a Markov-switching model under the assumption of a multi-level structure of regional economic system, and it is revealed that the regional cycle phase transition depends on the national cycle phase, but the propagation speed of the national phase into a regional cycle varies across the regions. In the second part, the national factor loadings on regional economies are estimated, and it is showed that the response of a regional economy to a national impact is mostly greater during a national contraction phase. In the last essay, since our observation of the regional economy depends on the scale of temporal/spatial units, even under the same underlying disaggregated level data generating process, we can encounter different neighborhood effects or spillovers. Thus, in this essay, the amount of spillover is defined by the forecast error variance decomposition (FEVD), and the direction of spillover is defined by the long-run sign of the cumulative impulse response function (CIRF). From an exercise using a constructed regional economic system, the size of spillover was found to decrease with spatial aggregation in a multi-level structure regional economic system. However, no monotonic trend was found in terms of the relative portion of positive/negative spillovers. In addition, the results from the real world data using different levels of aggregations, and the results drawn from the exercise on the constructed regional economic system are compared. From this comparison, a multi-level structure model which assumes the existence of higher level common factor affecting the regional units was found to concord with logical experiments conducted over the constructed regional economic system.

Graduation Semester

2015-5

Type of Resource

text

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Copyright 2015 Sungyup Chung

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