On firm-level,industry-level,and aggregate employment fluctuations

Employment fluctuations are examined, at different levels of aggregation, in a model with firm-specific hiring decisions due to search frictions and sticky pricing. The results indicate that firm-level employment dispersion rises with higher price stickiness and higher demand elasticity, whereas it falls with more convexity of search costs and with a higher labor supply elasticity. Industry-level employment is more volatile and less procyclical than aggregate employment, and a larger industry size reduces volatility and raises co-movement with output. The calibrated model is able to match the volatility, autocorrelation and cyclical correlation of US industry-level employment when incorporating firm-specific technology shocks.     

Self-reinforcing effects between housing prices and credit

The financial crisis has brought the interaction between housing prices and household borrowing into the limelight of the economic policy debate. This paper examines the nexus of housing prices and credit in Norway within a structural vector equilibrium correction model (SVECM) over the period 1986q2–2008q4. The results establish a two way interaction in the long-run, so that higher housing prices lead to a credit expansion, which in turn puts an upward pressure on prices. Interest rates influence housing prices indirectly through the credit channel. Furthermore, households’ expectations about the future development of their own income as well as in the Norwegian economy have a significant impact on housing price growth. Dynamic simulations show how shocks are propagated and amplified. When we augment the model to include the supply side of the housing market, these effects are dampened.     

Supply constraints and housing market dynamics

Although the volatility of house prices is often ascribed to demand-side factors, constraints on housing supply have important and little-studied implications for housing dynamics. I illustrate the strong relationship between the volatility of house prices and the regulation of new housing supply. I then employ a dynamic structural model of housing investment to investigate the mechanisms underlying this relationship. I find that supply constraints increase volatility through two channels: First, regulation lowers the elasticity of new housing supply by increasing lags in the permit process and adding to the cost of supplying new houses on the margin. Second, geographic limitations on the area available for building houses, such as steep slopes and water bodies, lead to less investment on average relative to the size of the existing housing stock, leaving less scope for the supply response to attenuate the effects of a demand shock. My estimates and simulations confirm that regulation and geographic constraints play critical and complementary roles in decreasing the responsiveness of investment to demand shocks, which in turn amplifies house price volatility.     

保障性住房供给中民间资本引导--以天津市为例

民间资本具有逐利性,民间资本参与保障性住房供给必然要追逐利益,相应的制度设计必须尊重民间资本的逐利性,给予民间资本稳定、持续的利益激励,从而保证其稳定、持续地参与保障性住房供给。但基于民间资本的流动性,需要在制度设计中中断民间资本的逐利性,避免民间资本参与保障性住房过程中为追逐利益而偏离住房保障目标。对于具有较高获益性的保障性住房,天津市允许民间资本直接参与供给;而在获益性较低的保障性住房项目中,天津市采用保障性住房投资基金、保障性住房信托投资基金、住房公积金贷款等工具鼓励民间资本参与保障性住房供给,有效地兼顾了民间资本的逐利性和保障性住房的公益性,在结果上达到了双赢。     

个人住房贷款政策对房地产市场的影响研究

金融政策的调整对房地产业发展具有重要影响,这一点在许多国家已经得到证实,在中国也逐步成为政府调节房地产业发展的手段。近年来,个人住房贷款政策随着房地产调控政策的出台而随之变化,本文研究中国个人住房贷款政策调整在对房地产市场的影响,并对如何促进房地产行业的发展,做出相关建议。     

浅析高校职工住房档案信息化管理

高校职工的住房呈现出多样化形式,住房档案也日益增多。在网络信息化时代,信息化是保存、管理和利用好职工住房档案,提高高校房产管理水平的有效方式。     

Sustainable Development and Resilience in Ecosystems

Two new important developments in environmental and resource economics is presented—non convex dynamics of ecosystems and wealth as an indicator of sustainable development. Non convex dynamics imply existence of resilience, that is the robustness of systems to withstand exogenous perturbations. Resilience can be regarded as an insurance against flips of the system into different basins of stability. Sustainable development, according to the Bruntland report, is the provision of productive resources to future generations to make it possible for them to live as well as the present generation. Thus, the value of changes in productive assets is therefore an index of whether an economy is on a sustainable path or not. Resilience can be regarded as one such productive asset and the paper discusses how one can define the value of this asset.     

Valuing ecosystem goods and services: a new approach using a surrogate market and the combination of a multiple criteria analysis and a Delphi panel to assign weights to the attributes

A new approach to valuing ecosystem goods and services (EGS) is described which incorporates components of the economic theory of value, the theory of valuation (USappraisal), a multi-model multiple criteria analysis (MCA) of ecosystem attributes, and a Delphi panel of experts to assign weights to the attributes. The total value of ecosystem goods and services in the various tenure categories in the Wet Tropics World Heritage Area (WTWHA) in Australia was found to be in the range AUD$188 to $211 million year⁻¹, or AUD$210 to 236 ha⁻¹ year⁻¹ across tenures, as at 30 June 2002. Application of the weightings assigned by the Delphi panelists and assessment of the ecological integrity of the various tenure categories resulted in values being derived for individual ecosystem services in the World Heritage Area. Biodiversity and refugia were the two attributes ranked most highly at AUD$18.6 to $20.9 million year⁻¹ and AUD$16.6 to $18.2 million year⁻¹, respectively.     

Noisy chaotic dynamics in commodity markets

The nonlinear testing and modeling of economic and financial time series has increased substantially in recent years, enabling us to better understand market and price behavior, risk and the formation of expectations. Such tests have also been applied to commodity market behavior, providing evidence of heteroskedasticity, chaos, long memory, cyclicity, etc. The present evaluation of futures price behavior confirms that the resulting price movements can be random, suggesting noisy chaotic behavior. Prices could thus follow a mean process that is dynamic chaotic, coupled with a variance that follows a GARCH process. Our conclusion is that models of this type could be constructed to assist in forecasting prices in the short run but not over long run time periods.First version received: June 2001/Final version received: March 2003     

When was the U.S. housing downturn predictable? A comparison of univariate forecasting methods

This paper uses three classes of univariate time series techniques (ARIMA type models, switching regression models, and state-space/structural time series models) to forecast, on an ex post basis, the downturn in U.S. housing prices starting around 2006. The performance of the techniques is compared within each class and across classes by out-of-sample forecasts for a number of different forecast points prior to and during the downturn. Most forecasting models are able to predict a downturn in future home prices by mid 2006. Some state-space models can predict an impending downturn as early as June 2005. State-space/structural time series models tend to produce the most accurate forecasts, although they are not necessarily the models with the best in-sample fit.