How Reverse Merger Firms Raise Capital in PIPEs: Search Costs and Placement Agent Reputation

This paper proposes a simple regression-based method for reducing the complexity of decisions in the international procurement process. Based on foreign trade data, the method uses indicators, which allow a product specific cross-section and longitudinal-section valuation of the international competitiveness and the supplied product quality of all potential supplier countries. The method thus provides a variety of information for procurement departments, including the present level and the dynamic of competitiveness and product quality for the potential supplier countries within every product group of the international product nomenclature (Combined System and the Harmonised System). Potential supplier countries --the companies of which have proven to be particularly competitive in the different product quality stages-- are identified. This pre-selection of countries enables the companies to limit their search for potential suppliers to the selected supplier countries. High search costs are subsequently reduced and trend prognoses can be constructed.

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Is intertemporal price discrimination the cause of price dispersion in markets with low search costs?

Applied Economics Letters ◽

10.1080/13504851.2020.1789055 ◽

2020 ◽

pp. 1-4

Author(s):

Charlie Lindgren ◽

Sven-Olov Daunfeldt ◽

Niklas Rudholm ◽

Siril Yella

Keyword(s):

Price Discrimination ◽

Price Dispersion ◽

Search Costs ◽

Intertemporal Price Discrimination

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Online rental housing market representation and the digital reproduction of urban inequality

Environment and Planning A Economy and Space ◽

10.1177/0308518x19869678 ◽

2019 ◽

Vol 52 (2) ◽

pp. 449-468 ◽

Cited By ~ 6

Author(s):

Geoff Boeing

Keyword(s):

Housing Market ◽

Smart Cities ◽

Rental Housing ◽

Search Costs ◽

Poverty Rate ◽

The Internet ◽

Urban Inequality ◽

The Usa ◽

Housing Search ◽

Rental Housing Market

As the rental housing market moves online, the internet offers divergent possible futures: either the promise of more-equal access to information for previously marginalized homeseekers, or a reproduction of longstanding information inequalities. Biases in online listings’ representativeness could impact different communities’ access to housing search information, reinforcing traditional information segregation patterns through a digital divide. They could also circumscribe housing practitioners’ and researchers’ ability to draw broad market insights from listings to understand rental supply and affordability. This study examines millions of Craigslist rental listings across the USA and finds that they spatially concentrate and overrepresent whiter, wealthier, and better-educated communities. Other significant demographic differences exist in age, language, college enrollment, rent, poverty rate, and household size. Most cities’ online housing markets are digitally segregated by race and class, and we discuss various implications for residential mobility, community legibility, gentrification, housing voucher utilization, and automated monitoring and analytics in the smart cities paradigm. While Craigslist contains valuable crowdsourced data to better understand affordability and available rental supply in real time, it does not evenly represent all market segments. The internet promises information democratization, and online listings can reduce housing search costs and increase choice sets. However, technology access/preferences and information channel segregation can concentrate such information-broadcasting benefits in already-advantaged communities, reproducing traditional inequalities and reinforcing residential sorting and segregation dynamics. Technology platforms like Craigslist construct new institutions with the power to shape spatial economies, human interactions, and planners’ ability to monitor and respond to urban challenges.

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