Opportunities and risks in the residential sector during a green transition: House prices, energy renovations and rising energy prices

[EN] Transitioning to a low carbon economy implies both risks and opportunities in the Danish housing sector, which accounts for one fourth of Denmark’s CO2 emissions. We study the heterogeneous impacts on house prices of energy prices and energy refurbishments by combining micro-level data on sales and housing characteristics with geolocation data and data from the official mandatory energy rating and housing condition reports. While energy refurbishments are generally convenient in the long run due to large future flows of savings, households who do not plan to stay in the same housing unit for long do not have an incentive to renovate unless the refurbishment costs are reflected in the sale prices. Yet the extent to which refurbishment costs are reflected on sale prices might vary by housing, market, and refurbishment characteristics. We exploit machine learning tools both to preprocess geolocation data and to identify sources of effect heterogeneity. We find that most refurbishments will not increase sales prices enough to cover the costs. Those refurbishments whose price effect will cover are typically located in and around smaller towns and mid-sized cities, and other areas with higher population density and well-developed road networks connected to towns and cities. They are also cheap and have lower-than-average impact on CO2 emissions. Our results imply that private incentives may not be sufficient to facilitate climate change mitigation. We show that if home owners financed the most profitable refurbishments before selling, CO2 emissions of these houses would have decreased by only 13,000 tonnes per year, or less than 0.02 per cent of total Danish greenhouse emissions. Hence, there may be a scope for tax deductions and the allocation of subsidies for energy renovation among private households. We conclude that while opportunities for profitable energy renovations are concentrated in these areas, transitional risks are instead associated with peripheral rural areas, where both the exposure to rising energy prices and the risk of financing renovations is highest.Martinello, A.; Møller, N. (2022). Opportunities and risks in the residential sector during a green transition: House prices, energy renovations and rising energy prices. En 4th International Conference on Advanced Research Methods and Analytics (CARMA 2022). Editorial Universitat Politècnica de València. 277-277. http://hdl.handle.net/10251/18971327727

Dynamic refugee matching

Asylum seekers are often assigned to localities upon arrival using uninformed matching systems, which lead to inefficient and unfair allocations. This paper proposes an informed dynamic mechanism as an intuitive and easy-to-implement alternative. Our mechanism can be adopted in any dynamic refugee matching problem given locality-specific quotas and that asylum seekers map into specific categories. Any matching selected by the proposed mechanism is Pareto efficient, and envy between localities is bounded by a single asylum seeker. Our simulations show that the proposed mechanism outperforms uninformed mechanisms even in presence of severe misclassification error in the estimation of asylum seeker categories

Effect of temperature, precursor type and dripping time on the crystallite size of nano zno obtained by one-pot synthesis: 2(k) full factorial design analysis

The aim of this work was to determine the effect of temperature, precursor and dripping time on the crystallite size of ZnO nanoparticles synthesized by controlled precipitation according a 2k full factorial design. ZnCl2, Zn(NO3)2 and NaOH were used as precursors. After synthesis, the nano crystalline powder was characterized by XRD (Cu Kα), UV-Vis, and HR-TEM. The nano ZnO particles presented a crystallite size between 210 and 260 Å (HR-TEM and XRD). The results show that the crystallite size depends on the type of precursor and temperature of synthesis, but not on the dripping time

The Effect of Unexpected Inheritances on Wealth Accumulation: Precautionary Savings or Liquidity Constraints

Combining a Danish population panel of yearly administrative wealth reports with the unexpected timing of parental deaths, I show that heirs deplete the majority of their inheritance within ten years. However, while liquid assets quickly converge to their pre-inheritance levels, consistently with the predictions of a buffer-stock model of consumption, investments in housing and financial markets persist over time. Heirs exploit inheritances to accumulate housing equity if young, and precautionary savings if liquidity constrained. By estimating the causal effect of inheritance on wealth accumulation in the long run, this paper shows that specific wealth components serve different coexisting saving strategies

The Effects of Schooling on Wealth Accumulation Approaching Retirement

Education and wealth are positively correlated for individuals approaching retirement, but the direction of the causal relationship is ambiguous in theory and has not been identified in practice. We combine administrative data on individual total wealth with a reform expanding access to lower secondary school in Denmark in the 1950s, finding that schooling increases pension annuity claims but reduces the non-pension wealth of men in their 50's. These effects grow stronger as normal retirement age approaches. Labour market mechanisms are key, with schooling increasing job mobility, reducing housing equity, increasing leverage, and improving occupational pension benefits

Measurement error in income and schooling, and the bias of linear estimators

We propose a general framework for determining the extent of measurement error bias in OLS and IV estimators of linear models, while allowing for measurement error in the validation source. We apply this method by validating Survey of Health, Ageing and Retirement in Europe (SHARE) data with Danish administrative registers.Contrary to most validation studies, we find measurement error in income is classical, once we account for imperfect validation data. We find non-classical measurement error in schooling, causing a 38 percent amplification bias in IV estimators of the returns, with important implications for the program evaluation literature