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1 – 2 of 2Evangelos Vasileiou, Elroi Hadad and Georgios Melekos
The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables…
Abstract
Purpose
The objective of this paper is to examine the determinants of the Greek house market during the period 2006–2022 using not only economic variables but also behavioral variables, taking advantage of available information on the volume of Google searches. In order to quantify the behavioral variables, we implement a Python code using the Pytrends 4.9.2 library.
Design/methodology/approach
In our study, we assert that models relying solely on economic variables, such as GDP growth, mortgage interest rates and inflation, may lack precision compared to those that integrate behavioral indicators. Recognizing the importance of behavioral insights, we incorporate Google Trends data as a key behavioral indicator, aiming to enhance our understanding of market dynamics by capturing online interest in Greek real estate through searches related to house prices, sales and related topics. To quantify our behavioral indicators, we utilize a Python code leveraging Pytrends, enabling us to extract relevant queries for global and local searches. We employ the EGARCH(1,1) model on the Greek house price index, testing several macroeconomic variables alongside our Google Trends indexes to explain housing returns.
Findings
Our findings show that in some cases the relationship between economic variables, such as inflation and mortgage rates, and house prices is not always consistent with the theory because we should highlight the special conditions of the examined country. The country of our sample, Greece, presents the special case of a country with severe sovereign debt issues, which at the same time has the privilege to have a strong currency and the support and the obligations of being an EU/EMU member.
Practical implications
The results suggest that Google Trends can be a valuable tool for academics and practitioners in order to understand what drives house prices. However, further research should be carried out on this topic, for example, causality relationships, to gain deeper insight into the possibilities and limitations of using such tools in analyzing housing market trends.
Originality/value
This is the first paper, to the best of our knowledge, that examines the benefits of Google Trends in studying the Greek house market.
Details
Keywords
Haya Al-Dajani, Nupur Pavan Bang, Rodrigo Basco, Andrea Calabrò, Jeremy Chi Yeung Cheng, Eric Clinton, Joshua J. Daspit, Alfredo De Massis, Allan Discua Cruz, Lucia Garcia-Lorenzo, William B. Gartner, Olivier Germain, Silvia Gherardi, Jenny Helin, Miguel Imas, Sarah Jack, Maura McAdam, Miruna Radu-Lefebvre, Paola Rovelli, Malin Tillmar, Mariateresa Torchia, Karen Verduijn and Friederike Welter
This conceptual, multi-voiced paper aims to collectively explore and theorize family entrepreneuring, which is a research stream dedicated to investigating the emergence and…
Abstract
Purpose
This conceptual, multi-voiced paper aims to collectively explore and theorize family entrepreneuring, which is a research stream dedicated to investigating the emergence and becoming of entrepreneurial phenomena in business families and family firms.
Design/methodology/approach
Because of the novelty of this research stream, the authors asked 20 scholars in entrepreneurship and family business to reflect on topics, methods and issues that should be addressed to move this field forward.
Findings
Authors highlight key challenges and point to new research directions for understanding family entrepreneuring in relation to issues such as agency, processualism and context.
Originality/value
This study offers a compilation of multiple perspectives and leverage recent developments in the fields of entrepreneurship and family business to advance research on family entrepreneuring.
Details