Adjustment Costs and Factor Demand: New Evidence from Firms’ Real Estate

Bergeaud, Antonin; Ray, Simon

doi:10.1093/ej/ueaa094

Cited by 12 publications

(8 citation statements)

References 59 publications

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“…The coefficients of the error‐correction terms are all significantly negative and in the range of zero and minus one, confirming that a long‐run equilibrium exists and that q , and, therefore, markups, gravitate toward stable long‐run equilibriums. The half‐way cycle is reached after approximately 3 years, suggesting relatively low capital adjustment costs of existing and new firms, a result that is consistent with the adjustment costs found in the literature (see, e.g., Bergeaud and Ray 2021).…”

Section: Empiricssupporting

confidence: 88%

Markups, Tobin's q, and the Increasing Capital Share

KERSPIEN¹,

Madsen²

2023

J of Money Credit Banking

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Increasing markups have recently gained prominence as a leading explanation for the increasing share of income going to capital since the 1980s. However, the existing analysis has been limited to the United States, covers only short periods, and generally does not control for potentially important confounders. Constructing data for the share of income going to capital and markups based on Tobin's q over the period 1870–2018 for 21 advanced countries, this research examines the ability of markups to explain the movements of income shares and the tendency for factor shares to converge toward constants in the long run. We find strong support for the markup hypothesis.

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Section: Empiricssupporting

confidence: 88%

Markups, Tobin's q, and the Increasing Capital Share

KERSPIEN¹,

Madsen²

2023

J of Money Credit Banking

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“…First, real estate is an important asset class for firms and serves multiple functions either as a productive asset or as a collateral for raising external finance (Chaney et al, 2012;Fougère et al, 2019). It is also an important source of friction that limits capital adjustments and employment dynamics of firms (Bergeaud and Ray, 2021). Second, it constitutes a central class of assets in financial markets, and any imbalance in this sector tends to decrease financial stability.…”

Section: Introductionmentioning

confidence: 99%

Working from home and corporate real estate

Bergeaud

Eyméoud

Garcia

et al. 2023

Regional Science and Urban Economics

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“…More complex relationships or changes will arise from the superposition of different factors. Therefore, with reference to the research experience of Bergeaud [88], Yan [89], Carrasco-Gallego [90], McMillan [91], Warsame [92], Oikarinen [93], Sun [94], and Hardie [95] et al, and based on the data accessibility, comparability, and completeness, we have explored the driving mechanisms of spatial inequality in the housing market (see Table 2) with 23 indicators as independent variables from four dimensions: economic level, social conditions, industrial structure, service, and infrastructure environment.…”

Section: Index Selectionmentioning

confidence: 99%

Spatial Inequality in China’s Housing Market and the Driving Mechanism

Zhao

Zhang

2021

Land

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Housing inequality is a widespread phenomenon around the world, and it varies widely across countries and regions. The housing market is naturally spatial in its attributes, and with the transformation of China’s urbanization, industrialization, and globalization, the spatial inequality in the housing market is increasingly severe. According to the geospatial differences in the housing market supply, demand, and price, and by integrating the influencing factors of economic, social, innovation, facility environment, and structural adjustment, this paper constructs a “spatial–supply–demand–price” integrated housing market inequality research framework based on the methods of CV, GI, and Geodetector, and it empirically studies the spatial inequality of provincial housing markets in China. The findings show that the spatial inequality in China’s housing market is significant and becomes increasingly serious. According to the study, we have confirmed the following. (1) Different factors vary greatly in influence, and they can be classified into three types, that is, “Key factors”, “Important factors”, and “Auxiliary factors”. (2) The spatial inequalities in housing supply, demand, and price vary widely in their driving mechanisms, but factors such as the added value of the tertiary industry, number of patents granted, and revenue affect all these three at the same time and have a comprehensive influence on the development and evolution of spatial inequalities in the housing market. (3) All the factors are bifactor-enhanced or non-linearly enhanced in relationships between every pair, and they are classified into three categories of high, medium, and low according to the mean of interacting forces; in particular, the factors of GDP, expenditure, permanent resident population, number of medical beds, and full-time equivalent of R&D personnel are in a stronger interaction with other factors. (4) Based on housing supply, demand, price, and their coordination, 31 provinces are classified into four types of policy zones, and the driving mechanisms of spatial inequalities in the housing market are further applied to put forward suggestions on policy design, which provides useful references for China and other countries to deal with housing spatial inequality.

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Adjustment Costs and Factor Demand: New Evidence from Firms’ Real Estate

Cited by 12 publications

References 59 publications

Markups, Tobin's q, and the Increasing Capital Share

Markups, Tobin's q, and the Increasing Capital Share

Working from home and corporate real estate

Spatial Inequality in China’s Housing Market and the Driving Mechanism

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