Spatial econometrics and the Lasso estimator : theory and applications

This thesis links two topics of empirical economics: spatial econometrics and the Lasso estimator. Spatial econometrics is concerned with methods and models accounting for interaction effects between units. The Lasso estimator is a regularisation technique that allows for simultaneous variable selection and estimation in a high dimensional setting where the number of parameters may exceed the sample size. Three applied and theoretical articles are presented that demonstrate how spatial econometric research can benefit from high-dimensional methods and, specifically, the Lasso. The introduction in Chapter 1 presents a literature review of both fields and discusses the connections between the two topics. Chapter 2 examines the effect of economic growth on civil conflicts in Africa. The Lasso estimator is employed to generate instrumental variables, which account for non-linearity and spatial heterogeneity. The theoretical contribution in Chapter 3 proposes a two-step Lasso estimator that can consistently estimate the spatial weights matrix in a spatial autoregressive panel model. Chapter 4 is an application to the US housing market. A Lasso-based estimation method is considered that controls for spatial effects in a spatial error-correction model. Chapter 5 provides concluding remarks

Spatial econometrics and the Lasso estimator : theory and applications

This thesis links two topics of empirical economics: spatial econometrics and the Lasso estimator. Spatial econometrics is concerned with methods and models accounting for interaction effects between units. The Lasso estimator is a regularisation technique that allows for simultaneous variable selection and estimation in a high dimensional setting where the number of parameters may exceed the sample size. Three applied and theoretical articles are presented that demonstrate how spatial econometric research can benefit from high-dimensional methods and, specifically, the Lasso. The introduction in Chapter 1 presents a literature review of both fields and discusses the connections between the two topics. Chapter 2 examines the effect of economic growth on civil conflicts in Africa. The Lasso estimator is employed to generate instrumental variables, which account for non-linearity and spatial heterogeneity. The theoretical contribution in Chapter 3 proposes a two-step Lasso estimator that can consistently estimate the spatial weights matrix in a spatial autoregressive panel model. Chapter 4 is an application to the US housing market. A Lasso-based estimation method is considered that controls for spatial effects in a spatial error-correction model. Chapter 5 provides concluding remarks

Price regulation, inflation, and nominal rigidity in housing rents. ESRI Working Paper No. 648 December 2019

In this paper, we explore the impact of a housing rent inflation cap of 4 per cent on price changes for tenancy contracts. We assess the implications of the regulations on the share of the market experiencing: 1) a price decline; 2) unchanged rents (nominal rigidity); 3) a positive growth rate below the cap; 4) the maximum allowable growth; and 5) growth above the cap. Our identification strategy uses a multinomial logit difference-in-difference approach applied to a novel micro panel dataset at the property level in Ireland. We find the overall inflation rate fell by 3 percentage points following the regulations, driven by a reduction in the share of individual contracts pricing above the regulatory maximum. We find an increase in the likelihood of nominal rigidity at the expense of high-growth rates. However, we also find a higher probability of small increases, at or below the regulatory level, relative to nominal rigidity after the regulations which is consistent with landlords trying to maintain real returns as price resets are not allowed between tenancies. Heterogeneous effects by landlord type and starting rent levels are evident

Urban rents and commuting times in Ireland. ESRI Research Bulletin 202018 September 2020.

City workers often face a choice between paying high housing costs to live close to work or making long commutes from areas with lower costs of accommodation. This paper measures the association between urban rents and commuting times in Ireland using data from recent years when rents rose substantially

Research on the Environment, Health, Consumer Behaviour and the Economy: ESRI Environment Research Programme 2018–2020. ESRI Report November 2020.

Continuing the partnership established between the Economic and Social Research Institute (ESRI) and the Environmental Protection Agency (EPA) in phase I (2016–2018) of the programme, this report summarises the findings from the second phase of the programme (2018–2020). A diverse set of research topics was examined, broadly grouped under five thematic areas

ddml: Double/debiased machine learning in Stata

We introduce the package ddml for Double/Debiased Machine Learning (DDML) in Stata. Estimators of causal parameters for five different econometric models are supported, allowing for flexible estimation of causal effects of endogenous variables in settings with unknown functional forms and/or many exogenous variables. ddml is compatible with many existing supervised machine learning programs in Stata. We recommend using DDML in combination with stacking estimation which combines multiple machine learners into a final predictor. We provide Monte Carlo evidence to support our recommendation.Comment: The package can be installed from https://github.com/aahrens1/ddml

Modellgestützte Politikberatung im Naturschutz: Zur „optimalen“ Flächennutzung in der Agrarlandschaft des Biosphärenreservates „Mittlere Elbe“

Using the example of the MAB Biosphere Preserve “Mittlere Elbeâ€, this article demonstrates how an “optimal†land-use pattern – a pattern aimed at combining ecological, economic and social objectives in an adequate way – can be determined. The focus is on the definition of alternative nature conservation approaches, the scenario technique, the definition of landscape functions, the utility analysis and the adaptive conjoint analysis. In addition, the authors demonstrate which quantitative methods can be used to obtain the information needed for utility and conjoint analyses on the ecological and economic effects of the conservation scenarios as well as on the weighting of the landscape functions, and how they can be integrated. Finally, it is shown that the conflict between ecological and economic objectives cannot only be reduced by a regional differentiation of the extent of resource protection – as shown in the literature –, but also by a spatial variation of the type of environment conservation.utility analysis, Conjoint analysis, riverside protection, nature conservation models, conservation scenarios, MAB Biophere Reserves, landscape function, optimal land use, Repertory Grid technique, Environmental Economics and Policy, Land Economics/Use,

The Influence of Elementary Silver Versus Titanium on Osteoblasts Behaviour In Vitro Using Human Osteosarcoma Cell Lines

Purpose. The antimicrobial effect of a silver-coated tumor endoprosthesis has been proven in clinical and experimental trials. However, in the literature there are no reports concerning the effect of elementary silver on osteoblast behaviour. Therefore, the prosthetic stem was not silver-coated because of concerns regarding a possible inhibition of the osseointegration. The aim of the present study was to investigate the effect of 5–25 mg of elementary silver in comparison to Ti-6Al-4V on human osteosarcoma cell lines (HOS-58, SAOS). Methods. Cell viability was determined by measuring the MTT proliferation rate. Cell function was studied by measuring alkaline phosphatase (AP) activity and osteocalcine production. Results. In the HOS-58 cells, the AP activity was statistically significant (P < 0.05) higher at a supplement of 5–10 mg of silver than of Ti-6 Al-4V at the same doses. For both cell lines, a supplement above 10 mg of silver resulted in a reduced AP activity in comparision to the Ti-6 Al-4V group, but a statistically significant difference (P < 0.05) was observed at a dose of 25 mg for the SAOS cells only. At doses of 20–25 mg in the HOS-58 cells and 10–25 mg in the SAOS cells, the reduction of the proliferation rate by silver was statistically significant (P < 0.05) compared to the Ti-6 Al-4V supplement. Discussion. In conclusion, elementary silver exhibits no cytotoxicity at low concentrations. In contrast, it seems to be superior to Ti-6 Al-4V concerning the stimulation of osteogenic maturation at these concentrations, whereas at higher doses it causes the known cytotoxic properties

Framework and baseline examination of the German National Cohort (NAKO)

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19–74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2–3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4–5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10654-022-00890-5