Speech is Silver, Silence is Gold: Trade-offs between Local and National Representation
Project description
This project uses natural language processing together with novel data on politicians to study the effect of strong party discipline on MPs' representation of local interests in parliament.
Dataset
Local and national historic unemployment (www.nav.no), descriptive statistics on districts (www.ssb.no), politicians' backgrounds (www.jon.fiva.no), parliamentary speeches (www.stortinget.no), travel bills (Stortinget), google trends (https://trends.google.com/trends/?geo=NO)
Are BI the sole data controller?: Yes
Joint data controllers: No
Data shared outside of BI: No
Are data to be transferred outside of EU/EEA or to an international organization: No
Data is shared with and/or transferred to: No
Personal data: Sensitive
Duration: End of project 15.02.2024
Project leader: Oda Nedregård
Project leader e-mail: oda.nedregard@bi.no
Frictions in the Housing Market
Project description
The housing market is key for understanding financial and banking crises. Similar to other financial markets, the housing market exhibits excess volatility - house prices are more volatile relative to both rental prices and aggregate income. Furthermore, a large share of the banks’ collateral is housing. One of the objectives of this project is to look for direct evidence on whether the transaction sequence choices of moving homeowners - the choice between “buying first” (and then selling) and “selling first” (and then buying) -- is an important contributing factor to house price volatility. In addition, we would like to understand whether changes in credit market conditions market conditions such as the availability of cheap short-term bridge loans may affect housing market conditions through the transaction sequence decisions of moving owners.
Dataset
All individuals that are 18 years old or above (as of December 31st of a given year) that have been involved in changes of real estate ownership in Oslo, Bærum, Stavanger and Bergen municipalities during the period 01.01.1993-09.02.2019. These individuals are extracted from the Land Register (Grunnboken) by AMBITA AS. The Land Register is publicly available register data. AMBITA is the owner of the extracted data. The data will then be merged with income and wealth register data by SSB. All individuals that are 18 years old or above (as of December 31st of a given year) that have been involved in changes of real estate ownership in Akershus, Trondheim, Sandnes, Sola, and Randaberg municipalities in the period 01.01.1993-31.08.2019. These individuals are extracted from the Land Register (Grunnboken) by AMBITA AS. The Land Register is publicly available register data. AMBITA is the owner of the extracted data.
Are BI the sole data controller?: Yes
Joint data controllers:
Data shared outside of BI: No
Are data to be transferred outside of EU/EEA or to an international organization: No
Data is shared with and/or transferred to: No
Personal data: General
Duration: 28.02.2018 until publication of the results of the project (likely 31.12.2024).
Project leader: Espen R. Moen
Project leader e-mail: espen.r.moen@bi.no
The dynamics of political selection
Project description
Democracies around the world are being confronted with serious public policy challenges, including the increasingly global ramifications of economic and human interconnectedness related to migration and social justice, health threats from pandemic diseases, and climate change. The vast capabilities of the modern state allow political leaders to exert wide-ranging positive—and negative—influence over social and economic developments, and political parties are the core institutions responsible for recruiting, selecting, and promoting these leaders. It is therefore critically important to understand how parties organize this selection process, and how career incentives shape the identity and behavior of political elites. Our project aims to explore institutionalized selection within political parties as an ongoing process that occurs throughout a politician’s entire career. This dynamic view raises several important topics that a static approach (such as studying candidate nominations alone) does not: Do all citizens of comparable quality have a fair chance of rising in the political hierarchy? Can members from the established elite, such as dynastic candidates, leapfrog career steps and seniority rules? Are candidates from underrepresented groups, such as women, disadvantaged by these same career systems? How do parties incentivize candidates to induce effort? These are some of the questions that we aim to answer in our project.
Dataset
Fiva and Smith (2017) introduce a new dataset featuring all candidates running for Norwegian parliamentary elections from 1906 to 2013 (later extended to 2021). Fiva, Vøllo and Sørensen (2020) build a similar candidate-level data set covering local (municipal and county) elections in Norway during the 1971 to 2019 period. Collection of these data has been evaluated by Sikt, previously known as the Norwegian centre for research data (NSD), to be in line with the Personal Data Act (Personopplysningsloven) and is available for researchers at http://www.jon.fiva.no/data.htm. The candidate-level data from Fiva and Smith (2017) and Fiva, Vøllo and Sørensen (2020), as well as data about politicians holding higher offices, have been linked to administrative registers in Statistics Norway. In the final datasets the national ID number has been replaced by a project-specific pseudonymous identifier that is similarly applied to the other individual-level data sources used. Moreover, names and other directly identifying information are removed from the analysis file by a third party, namely Statistics Norway. In this way, the researcher cannot observe sensitive information on particular individuals in the analysis phase. Moreover, research results will be reported at the aggregate level in such a manner that no individual can be directly or indirectly identified from the final tables.
Are BI the sole data controller?: Yes
Joint data controllers: No
Data shared outside of BI: No
Are data to be transferred outside of EU/EEA or to an international organization: No
Data is shared with and/or transferred to: No
Personal data: Sensitive and details of criminal offences
Duration: 01.08.2021-31.07.2028
Project leader: Jon H. Fiva
Project leader e-mail: jon.h.fiva@bi.no
Analysis of labormarket outcomes: mobility, trade and human capital.
Project description
The overall purpose of the project is to study mobility and dynamics in the labor market and the housing market. The project consists of seven parts. Each part will analyze the overall question based on different perspectives: How a flexible labor market can more easily handle the downturn (subproject 1), the importance of entrepreneurship and immigrant skills (subproject 2), geographical proximity to the family as a condition for young children's participation (subproject 3), the importance of higher education for the success of marginal students in the labor market (subproject 4), the importance of fluctuations in the housing market for financial crises (subproject 5), vacancies, job search, and matching in the labor market (subproject 6), and the importance of non-cognitive abilities for labor market outcomes (subproject 7).
Dataset
The data material is mainly obtained from Statistics Norway's register data. Four of the projects combine Statistics Norway data with other data: Project 4 uses data from BI's student administrative registers, project 5 uses data on real estate transactions, project 6 uses data from NAV on job change and job search, and project 7 uses data on personality traits obtained through experiments performed in PC laboratory.
Are BI the sole data controller?: Yes
Joint data controllers: No
Data shared outside of BI: No
Are data to be transferred outside of EU/EEA or to an international organization: No
Data is shared with and/or transferred to: No
Duration: The project will start in 2022 and is estimated to be finished in 2027, but we are planning to add new data after this timepoint as well.
Personal data: General
Project leader: Espen R. Moen
Project leader e-mail: espen.r.moen@bi.no