Stata do-file for the paper informal legacy and exporting among Sub-Saharan African firms

Stata do-file for the paper informal legacy and exporting among Sub-Saharan African firms. Published in Organization Science (2022). Abstract paper Around the world and especially in areas of widespread poverty, firms start their operations without registering with relevant authorities (i.e., in the informal economy). We explore whether firms that initiated their operations in the informal economy but later register have a higher propensity to export than firms that register at the time of their foundation. We reason that the experience of having operated informally provides formally registered firms with the advantage of low-cost and flexible exploration but also a domestic legitimacy liability. We suggest that these factors likely contribute to making foreign export markets more attractive after registration. Based on a comprehensive sample of Sub-Saharan African firms, we find that conditional on registration, firms with an informal legacy have a higher propensity to initiate exporting than firms that started their operations formally. We contribute with theoretical and policy-oriented insights on the dynamics of informality and exporting. This stata do-file lists all commands that have been executed in the data management and analysis process. The main data source is the World Bank Enterprise Survey. World Bank Enterprise Survey Data is available through the World Bank for researchers after registration. Reference: Larsen, M. M., & Witte, C. T. (2022). Informal Legacy and Exporting Among Sub-Saharan African Firms. Organization Science

Stata do-file for the paper informal legacy and exporting among Sub-Saharan African firms

Stata do-file for the paper informal legacy and exporting among Sub-Saharan African firms. Published in Organization Science (2022). Abstract paper Around the world and especially in areas of widespread poverty, firms start their operations without registering with relevant authorities (i.e., in the informal economy). We explore whether firms that initiated their operations in the informal economy but later register have a higher propensity to export than firms that register at the time of their foundation. We reason that the experience of having operated informally provides formally registered firms with the advantage of low-cost and flexible exploration but also a domestic legitimacy liability. We suggest that these factors likely contribute to making foreign export markets more attractive after registration. Based on a comprehensive sample of Sub-Saharan African firms, we find that conditional on registration, firms with an informal legacy have a higher propensity to initiate exporting than firms that started their operations formally. We contribute with theoretical and policy-oriented insights on the dynamics of informality and exporting. This stata do-file lists all commands that have been executed in the data management and analysis process. The main data source is the World Bank Enterprise Survey. World Bank Enterprise Survey Data is available through the World Bank for researchers after registration. Reference: Larsen, M. M., & Witte, C. T. (2022). Informal Legacy and Exporting Among Sub-Saharan African Firms. Organization Science

Replication package for "Fully Autonomous Programming with Large Language Models"

This repository contains the replication package for the paper "Fully Autonomous Programming with Large Language Models", Vadim Liventsev, Anastasiia Grishina, Aki Härmä, and Leon Moonen, accepted for the 2023 ACM SIGEVO Genetic and Evolutionary Computation Conference (GECCO'23). The paper is deposited on arXiv, will be available at the publisher's site, and a copy is included in this repository. The replication package is archived on Zenodo with DOI: 10.5281/zenodo.7837282. The source code is distributed under the MIT license, the data is distributed under the CC BY 4.0 license. Organization The repository is organized as follows: Archived source code in the src folder, with a dedicated README. Analysis of the results in the analysis folder, with a dedicated README. Archive of SEIDR-generated solutions for PSB2 as a git bundle: psb2-solutions.bundle. These solutions can be inspected by cloning the bundle using git clone psb2-solutions.bundle which will create a folder psb2-solutions with a dedicated README in the master branch. The other branches contain the code that was generated in specific experiments/configurations. List which experiments are available using git branch -r, select one using git checkout , and look at the iteratively synthesized solution for a problem using git log -p -- {problem}.{cpp/py}. Alternatively, these can be inspected on GitHub. Citation If you build on this data or code, please cite this work by referring to the paper: @inproceedings{liventsev2023:fully, title = {Fully Autonomous Programming with Large Language Models}, author = {Vadim Liventsev and Anastasiia Grishina and Aki Härmä and Leon Moonen}, booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO'23)}, year = {2023}, publisher = {ACM} doi = {https://doi.org/10.1145/3583131.3590481}, } External References The SEIDR source code is maintained on GitHub. The SEIDR-generated solutions for PSB2 are versioned on GitHub as well

Joint EVS/WVS 2017-2021 Dataset (Joint EVS/WVS)

The European Values Study (EVS) and the World Values Survey (WVS) are two large-scale, cross-national and longitudinal survey research programmes. They include a large number of questions on moral, religious, social, political, occupational and family values which have been replicated since the early eighties. Both organizations agreed to cooperate in joint data collection from 2017. EVS has been responsible for planning and conducting surveys in European countries, using the EVS questionnaire and EVS methodological guidelines. WVSA has been responsible for planning and conducting surveys in countries in the world outside Europe, using the WVS questionnaire and WVS methodological guidelines. Both organisations developed their draft master questionnaires independently. The joint items define the Common Core of both questionnaires. The Joint EVS/WVS is constructed from the two EVS and WVS source datasets: - European Values Study 2017 Integrated Dataset (EVS 2017), ZA7500 Data file Version 4.0.0, doi:10.4232/1.13560 (https://doi.org/10.4232/1.13560). - European Values Study 2017: Ukraine (EVS 2017), ZA7539 Data file Version 1.0.0, doi:10.4232/1.13714 (https://doi.org/10.4232/1.13714). - World Values Survey: Round Seven–Country-Pooled Datafile. Version 2.0.0, doi: 10.14281/18241.13 (https://doi.org/10.14281/18241.13).The European Values Study (EVS) and the World Values Survey (WVS) are two large-scale, cross-national and longitudinal survey research programmes. They include a large number of questions on moral, religious, social, political, occupational and family values which have been replicated since the early eighties. Both organizations agreed to cooperate in joint data collection from 2017. EVS has been responsible for planning and conducting surveys in European countries, using the EVS questionnaire and EVS methodological guidelines. WVSA has been responsible for planning and conducting surveys in countries in the world outside Europe, using the WVS questionnaire and WVS methodological guidelines. Both organisations developed their draft master questionnaires independently. The joint items define the Common Core of both questionnaires. The Joint EVS/WVS is constructed from the two EVS and WVS source datasets: - European Values Study 2017 Integrated Dataset (EVS 2017), ZA7500 Data file Version 4.0.0, doi:10.4232/1.13560 (https://doi.org/10.4232/1.13560). - European Values Study 2017: Ukraine (EVS 2017), ZA7539 Data file Version 1.0.0, doi:10.4232/1.13714 (https://doi.org/10.4232/1.13714). - World Values Survey: Round Seven–Country-Pooled Datafile. Version 2.0.0, doi: 10.14281/18241.13 (https://doi.org/10.14281/18241.13)

EVS Trend File 1981-2017 – Sensitive Dataset

The European Values Study is a large-scale, cross-national and longitudinal survey research program on how Europeans think about family, work, religion, politics, and society. Repeated every nine years in an increasing number of countries, the survey provides insights into the ideas, beliefs, preferences, attitudes, values, and opinions of citizens all over Europe. The EVS Trend File 1981-2017 is constructed from the five EVS waves and covers almost 40 years. In altogether 160 surveys, more than 224.000 respondents from 48 countries/regions were interviewed. It is based on the updated data of the EVS Longitudinal Data File 1981-2008 (v.3.1.0) and the current EVS 2017 Integrated Dataset (v.5.0.0). For the EVS Trend File, a Restricted-Use File (ZA7504) is available in addition to the (factually anonymised) Scientific-Use File (ZA7503). The EVS Trend File – Sensitive Dataset (ZA7504) is provided as an add-on file. In addition to a small set of admin and protocol variables needed to merge with the SUF data, the Sensitive Dataset contains the following variables that could not be included in the scientific-use file due to their sensitive nature: W005_3 Job profession/industry (3-digit ISCO88) - spouse/partner EVS 2008W005_3_01 Job profession/industry (3-digit ISCO08) - spouse/partner EVS 2017W005_4 Job profession/industry (4-digit ISCO88) - spouse/partner EVS 2008X035_3 Job profession/industry (3-digit ISCO88) – respondent EVS 1999, EVS 2008 X035_3_01 Job profession/industry (3-digit ISCO08) - respondent EVS 2017X035_4 Job profession/industry (4-digit ISCO88) – respondent EVS 1999, EVS 2008 x048c_n3 Region where the interview was conducted (NUTS-3): NUTS version 2006 EVS 2008X048J_N3 Region where the interview was conducted (NUTS-3): NUTS version 2016 EVS 2017X049 Size of town (8 categories) EVS 2008, EVS 2017 Detailed information on the anonymization process in the EVS Trend File is provided in the EVS Trend File Variable Report