Online retailing is growing rapidly and customer retention has become increasingly important, especially trust and ecommerce institutional mechanisms such as online credit card guarantees, escrow services, and privacy protection, which have become more significant and the subject of recent research (Fang et al., 2014). We conducted a methodological replication of first insights and a model of the relation between satisfaction, trust, repurchase intention and the perceived effectiveness of such e-commerce institutional mechanisms (PEEIM). As we were unable to support the original findings, we provide an alternative reasoning relevant to today's role of PEEIM for online repurchases and discuss implications for research and practice.
Purpose
This paper aims to investigate the relationship between residential real estate prices and unemployment rates at the Metropolitan Statistical Area (MSA) level.
Design/methodology/approach
This paper uses a long time-series of MSA-level quarterly data from 1990 to 2018. It uses an instrumental variable approach to estimate the effects of residential real estate prices on unemployment rates using the geography-based land constraints measure of Saiz (2010) as the instrument.
Findings
The results show that changes in residential real estate prices do not have a causal effect on unemployment rates in the same quarter. However, it takes 9-12 months for an increase (decrease) in real estate prices to decrease (increase) unemployment rates. This effect is significant during both pre- and post-financial crisis periods and robust to control for the economic characteristics of MSAs.
Research limitations/implications
This paper contributes to the emerging literature that studies the real effects of real estate. Particularly, the methodology and the findings can be used to investigate causal relationships between housing prices and small business development or economic growth. The findings are also of interest to policymakers and practitioners as they illustrate how and when real estate price shocks propagate to the real economy through unemployment rates.
Practical implications
This study’s findings have important implications for academics, policymakers and investors as they provide evidence of a snowball effect associated with shocks to real estate prices: increasing (decreasing) unemployment rates following a decrease (increase) in real estate prices exacerbates the real estate price movements and their economic consequences.
Originality/value
This paper analyzes a significantly longer period, from 1990 to 2018, than the existing literature. Additionally, it uses the MSA-level land unavailability measure of Saiz (2010) as an instrument to explore the effects of residential real estate prices on unemployment rates and when those effects are observed in the real economy.
In this paper, we use Google Trends data to proxy macro fundamentals that are related to two conventional structural determination of exchange rate models: purchasing power parity model and the monetary exchange rate determination model. We assess forecasting performance of Google Trends based models against random walk null on Turkish Lira–US Dollar exchange rate for the period of January 2004 to August 2015. We offer a three-step methodology for query selection for macro fundamentals in Turkey and the US. In out-of-sample forecasting, results show better performance against no-change random walk predictions for specifications both when we use Google Trends data as the only exchange rate predictor or augment it with exchange rate fundamentals. We also find that Google Trends data has limited predictive power when used in year-on-year growth rate format.
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