Media and Political Persuasion: Evidence from Russia

This paper compares electoral outcomes of 1999 parliamentary elections in Russia among geographical areas with differential access to the only independent from the government national TV channel. It was available to three-quarters of Russia’s population and its signal availability was idiosyncratic conditional on observables. Independent TV decreased aggregate vote for the government party by 8.9 percentage points, increased the combined vote for major opposition parties by 6.3 percentage points, and decreased turnout by 3.8 percentage points. The probability of voting for opposition parties increased for individuals who watched independent TV even controlling for voting intentions measured one month before elections.

Media and Political Persuasion: Evidence from Russia

How do media affect voting behavior? What difference can an independent media outlet make in a country with state-controlled media? Our paper addresses these questions by comparing electoral outcomes and votes reported by survey respondents during the 1999 parliamentary elections in Russia for those geographical areas that had access and those that had no access to the only national TV channel independent from the government (“NTV”). The effect is identified from exogenous variation in the availability of the signal, which appears to be mostly idiosyncratic, conditional on controls. The findings are as follows. 1) The presence of the independent TV channel decreased the aggregate vote for the government party by 2.5 percentage points and increased the combined vote for major opposition parties by 2.1 percentage points. 2) The probability of voting for opposition parties increased for individuals who watched NTV even controlling for voting intentions measured one month prior to the elections. 3) NTV had a smaller effect on votes of people with higher political knowledge and those using alternative sources of political news and a larger effect on retired persons who watch TV substantially more than working individuals.

Investor Return in REITs: Evidence of Market Timing and Capacity Constraints

This dissertation studies the returns earned in Real Estate Investment Trusts (REITs) from the point of view of the average investor. Traditional buy-and-hold returns while appropriate as a measure of return for financial asset may not adequately reflect the returns of the average individual investor because they do not take into account the capital flows in and out of an asset. Just as their name suggests, these are the returns one would earn if one buys a financial asset or portfolio at the beginning of a period and holds the investment until the end without making changes to the amount or composition of the investment. Most investors however make contributions, withdraw or rebalance their portfolios, making buy-and-hold returns unsuitable for measuring the returns of individual investors. Depending on how they time their cash flows, individual investors could perform significantly better or worse than the financial asset they are investing in. In addition capacity constrains to the return generating mechanism could be revealed as investors increase their cash involvement into an asset. Dollar weighted returns and dollar weighted average returns are alternative measures that accounts for all cash flows in and out of the investment. By contrasting investor centered returns to the conventional buy and hold returns this dissertation sheds light on the overall ability of investors to time the REIT market and the capacity constraints that they encounter

Semantic data mining and linked data for a recommender system in the AEC industry

Even though it can provide design teams with valuable performance insights and enhance decision-making, monitored building data is rarely reused in an effective feedback loop from operation to design. Data mining allows users to obtain such insights from the large datasets generated throughout the building life cycle. Furthermore, semantic web technologies allow to formally represent the built environment and retrieve knowledge in response to domain-specific requirements. Both approaches have independently established themselves as powerful aids in decision-making. Combining them can enrich data mining processes with domain knowledge and facilitate knowledge discovery, representation and reuse. In this article, we look into the available data mining techniques and investigate to what extent they can be fused with semantic web technologies to provide recommendations to the end user in performance-oriented design. We demonstrate an initial implementation of a linked data-based system for generation of recommendations