What is he best known for?
The fields of study he is best known for:
- Finance
- Macroeconomics
- Microeconomics
His primary areas of investigation include Econometrics, Real estate investment trust, Real estate, Financial economics and Valuation.
His work in Real estate investment trust addresses issues such as Equity, which are connected to fields such as Vector autoregression, Capital flows, Initial public offering and Information asymmetry.
His Real estate research includes themes of Systematic risk and Capital asset pricing model.
His Valuation research incorporates elements of Commercial mortgage-backed security, Monetary economics, Mortgage underwriting and Securities research.
Within one scientific family, David C. Ling focuses on topics pertaining to Consumption under Monetary economics, and may sometimes address concerns connected to Labour economics.
His research in Capitalization rate intersects with topics in Income approach and Cost approach.
His most cited work include:
- The Integration of Commercial Real Estate Markets and Stock Markets (218 citations)
- Valuation uncertainty, institutional involvement, and the underpricing of IPOs: The case of REITs (211 citations)
- Economic Risk Factors and Commercial Real Estate Returns (182 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Real estate, Real estate investment trust, Monetary economics, Financial economics and Finance.
His studies in Real estate integrate themes in fields like Capital asset pricing model, Asset and Depreciation.
David C. Ling has included themes like Equity, Econometrics, Market liquidity, Portfolio and Valuation in his Real estate investment trust study.
His study in Valuation is interdisciplinary in nature, drawing from both Initial public offering and Equity risk.
His work deals with themes such as Value, Capital, Leverage and Tax law, which intersect with Monetary economics.
His Capitalization rate study combines topics from a wide range of disciplines, such as Capital requirement and Cost approach.
He most often published in these fields:
- Real estate (46.79%)
- Real estate investment trust (33.97%)
- Monetary economics (30.77%)
What were the highlights of his more recent work (between 2016-2021)?
- Real estate (46.79%)
- Real estate investment trust (33.97%)
- Monetary economics (30.77%)
In recent papers he was focusing on the following fields of study:
David C. Ling mostly deals with Real estate, Real estate investment trust, Monetary economics, Portfolio and Finance.
In his research, David C. Ling undertakes multidisciplinary study on Real estate and Internal revenue.
His Real estate investment trust research includes elements of Enterprise value, Total return, Diversification and Equity.
His Monetary economics study integrates concerns from other disciplines, such as Capitalization rate, Recession and Debt.
His Portfolio study is concerned with the larger field of Financial economics.
His Finance research incorporates elements of Capital and Investment.
Between 2016 and 2021, his most popular works were:
- Search Costs, Behavioral Biases, and Information Intermediary Effects (25 citations)
- A First Look at the Impact of COVID-19 on Commercial Real Estate Prices: Asset-Level Evidence (22 citations)
- REIT Leverage and Return Performance: Keep Your Eye on the Target (15 citations)
In his most recent research, the most cited papers focused on:
- Finance
- Macroeconomics
- Microeconomics
David C. Ling focuses on Real estate investment trust, Financial economics, Real estate, Portfolio and Information asymmetry.
David C. Ling works mostly in the field of Real estate investment trust, limiting it down to topics relating to Equity and, in certain cases, Net asset value and Econometrics, as a part of the same area of interest.
His work in the fields of Financial economics, such as Total return, overlaps with other areas such as Apartment.
His studies deal with areas such as Percentage point, Shock and Capital market as well as Real estate.
In general Portfolio, his work in Performance attribution is often linked to Asset location, Large sample and Location linking many areas of study.
His studies in Information asymmetry integrate themes in fields like Quality, Price level and Search cost.
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