Macroeconomic Analysis Using Regional Data: An Application to Monetary Policy

Carlino, Gerald A.; DeFina, Robert H.

doi:10.1002/9780470996225.ch26

Cited by 5 publications

(4 citation statements)

References 6 publications

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“…Others focus on the time series properties of city-level house price data(Capozza et al 2002, Miller andPeng 2006). Another line of papers has concentrated on heterogeneity with regard to the reactions of city-level house prices to a monetary stimulus or shocks to aggregate macroeconomic variables(Himmelberg et al 2005, Carlino andDeFina 2008). Yet…”

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confidence: 99%

Aging and urban house prices

Hiller¹,

Lerbs

2016

Regional Science and Urban Economics

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Die Dis cus si on Pape rs die nen einer mög lichst schnel len Ver brei tung von neue ren For schungs arbei ten des ZEW. Die Bei trä ge lie gen in allei ni ger Ver ant wor tung der Auto ren und stel len nicht not wen di ger wei se die Mei nung des ZEW dar.Dis cus si on Papers are inten ded to make results of ZEW research prompt ly avai la ble to other eco no mists in order to encou ra ge dis cus si on and sug gesti ons for revi si ons. The aut hors are sole ly respon si ble for the con tents which do not neces sa ri ly repre sent the opi ni on of the ZEW. Aging and Urban House PricesNorbert Hiller AbstractThis paper investigates the long-run relationships between the size and age composition of a city's population and the price of local housing. For estimation purposes, we combine city-level demographic information with housing price data for 87 cities in Germany over the period 1995-2012. Employing a panel error correction framework that accounts for the evolution of city income and other controls, we find that urban house prices perform stronger in cities that grow or age less rapidly. A combination of the empirical estimates with current population projections suggests that population aging will exert considerable downward pressure on urban house prices in upcoming years.

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confidence: 99%

Aging and urban house prices

Hiller¹,

Lerbs

2016

Regional Science and Urban Economics

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“…Differences between these subregions can be used as data laboratories to examine macroeconomic theory and policy (cf. Carlino and DeFina, 2006). There are manifold reasons to be interested in identifying the spatial variation in the geographical distribution of outcomes, benefits and burdens of public policies; for example, it becomes possible to identify regions with favorable and unfavorable conditions (e.g.…”

Section: Introductionmentioning

confidence: 99%

Regionalization Heuristic to Map Spatial Heterogeneity of Macroeconomic Impacts: The Case of the Green Energy Transition in NRW

2019

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We discuss a vector-based regionalization heuristic to map the spatial variation of macroeconomic effects. Empirical regional studies of energy markets are often unfeasible due to a lack of data, particularly on demand and distribution infrastructure. The proposed heuristic is useful to model effects with high spatial heterogeneity and small overall net impact. As an illustration without loss of generality, we apply the heuristic to results from an input-output analysis on value creation effects by the energy transition in manufacturing sectors in the German federal state of North Rhine-Westphalia. The heuristic is applicable for regionalizing other macroresults, for example, from survey and other energy modeling studies.

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“…7 The housing market, however, is "regional." In particular, we assume that the agents in each region can only purchase and derive utility from the housing stock in the same region.…”

Section: Introductionmentioning

confidence: 99%

“…This paper attempts to focus on the aggregate implications for such difference and will therefore take the difference as given. 7 In principle, as one referee wisely observes, since history-dependent contingent claims are not available, the paths of the equilibrium price and quantities can be history dependent. In our numerical implementations, since we focus on the moments over a sample period rather than the exact time paths, we do not observe significant changes in results with different initial conditions.…”

Section: Introductionmentioning

confidence: 99%

Should the optimal portfolio be region-specific? A multi-region model with monetary policy and asset price co-movements

Leung

Teo

2011

Regional Science and Urban Economics

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Abstract:A multi-region, dynamic stochastic general equilibrium (MRDSGE) model is built to show that differences in the price elasticity of housing supply can be related to stylized facts on regional differences in (1) house price level, (2) house price volatility, (3) monetary policy propagation mechanism and (4) household asset portfolio. In addition, regional house prices are found to move more closely with regional fundamentals than with the national GDP. The correlation between the national stock price and the regional housing price also vary significantly across regions, which suggests that optimal portfolio should be region specific. JEL Classification Numbers: E32, E52, R10, R33

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Macroeconomic Analysis Using Regional Data: An Application to Monetary Policy

Cited by 5 publications

References 6 publications

Aging and urban house prices

Aging and urban house prices

Regionalization Heuristic to Map Spatial Heterogeneity of Macroeconomic Impacts: The Case of the Green Energy Transition in NRW

Should the optimal portfolio be region-specific? A multi-region model with monetary policy and asset price co-movements

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