Reading List - Githubissues

janbeering commented 1 month ago

War Economics:

[x] Masuhr, N. and Zogg, B. (2022). The war in ukraine: First lessons
[x] Mykhnenko, V., Delahaye, E., and Mehdi, N. (2022). Understanding forced internal displacement in ukraine: insights and lessons for today’s crises
[ ] EBRD (2022). Transition report 2022-23.
[x] Davis, D. R. and Weinstein, D. E. (2002). Bones, bombs, and break points: the geography of economic activity.
[x] Bellows, J. and Miguel, E. (2006). War and institutions: New evidence from sierra leone.
[x] Economist, T. and Solstad, S. (2023). The economist war-fire model. first published in the article ”a hail of destruction”. The Economist, February(25th).
[x] Nordhaus, W. D. (2002). The economic consequences of a war in iraq.
[x] Qadir, J., Ali, A., Zwitter, A., Sathiaseelan, A., Crowcroft, J., et al. (2016). Crisis analytics: big data-driven crisis response. Journal of International Humanitarian Action, 1(1):1–21.
[x] Fransen, S., Ruiz, I., and Vargas-Silva, C. (2017), ‘Return Migration and Economic Outcomes in the Conflict Context’, World Development, 95, 196–210.
[ ] Keynes, Robinson (1940) The Concept of National Income: A Supplementary Note
[x] Coyne (2020) Defense, Peace and War Economics
[x] Kimbrough (2017) War and Conflict in Economics -> Game-Theory
[x] Brauer (2017) - Of the Expence of Defence
[x] Federle, Meier, Müller, Mutschler, Schularick (2024) - THE PRICE OF WAR
[x] Acemoglu and Robinson (2001) - A Theory of Political Transitions
[x] Pigou (1939) - War Finance and Inflation
[x] Singer (1941) - The German War Economy
[ ] Fontane - The War in Ukraine
[ ] Keynes - The Economics of War in Germany
[ ] Lawrence (1915) - War Economics
[x] Maltsev - Economics of Military Innovation
[x] Schoenberger - War, Capitalism and the Making and Unmaking of Economics Geographies
[x] Solman (2008) - Economics of War - Economics 101 Teaching
[x] Tooze (2014) - World Economy and the Great War

janbeering commented 1 month ago

Nowcasting GDP Nightlight Intensity:

[ ] Addison, D. M. and Stewart, B. (2015). Nighttime lights revisited: the use of nighttime lights data as a proxy for economic variables. World Bank Policy Research Working Paper, (7496).
[ ] Armstrong, J. S. (2001). Combining forecasts. Principles of forecasting: A handbook for researchers and practitioners, pages 417–439.
[ ] Asher, S., Lunt, T., Matsuura, R., and Novosad, P. (2021). Development research at high geographic resolution: An analysis of night-lights, firms, and poverty in india using the SHRUG open data platform. The World Bank Economic Review, 35(4):845–871.
[ ] Bickenbach, F., Bode, E., Nunnenkamp, P., and S¨oder, M. (2016). Night lights and regional GDP. Review of World Economics, 152(2):425–447.
[ ] Chen, X. and Nordhaus, W. (2011). Using luminosity data as a proxy for economic statistics. Proceedings of the National Academy of Sciences, 108(21):8589–8594.
[ ] Croft, T. A. (1973). Burning waste gas in oil fields. Nature, 245(5425):375–376.
[ ] Croft, T. A. (1978). Nighttime images of the earth from space. Scientific American, 239(1):86–101.
[ ] Doll, C., Muller, J.-P., and Morley, J. (2006). Mapping regional economic activity from night-time light satellite imagery. Ecological Economics, 57(1):75–92.
[ ] Elvidge, C. D., Baugh, K. E., Kihn, E. A., Kroehl, H. W., Davis, E. R., and Davis, C. W. (1997). Relation between satellite observed visible-near infrared emissions, population, economic activity and electric power consumption. International Journal of Remote Sensing, 18(6):1373–1379.
[ ] Elvidge, C. D., Sutton, P. C., Ghosh, T., Tuttle, B. T., Baugh, K. E., Bhaduri, B., and Bright, E. (2009). A global poverty map derived from satellite data. Computers and Geosciences, 35(8):1652–1660.
[ ] Gibson, J., Olivia, S., Boe-Gibson, G., and Li, C. (2021). Which night lights data should we use in economics, and where? Journal of Development Economics, 149:102602.
[ ] Henderson, J., Storeygard, A., and Weil, D. (2012). Measuring economic growth from outer space. American Economic Review, 102(2):994–1028.
[ ] Henderson, V., Storeygard, A., and Weil, D. (2011). A bright idea for measuring economic growth. American Economic Review, 101(3):194–199.
[ ] Lazar, M. (2010). Shedding light on the global distribution of economic activity. The Open Geography Journal, 3(1):147–160.
[ ] Min, B., Baugh, K., Monroe, T., Goldblatt, R., andn Walker Kosmidou-Bradley, B. S., and Crull, D. (2021). Light every night – new nighttime light data set and tools for development. Technical report, World Bank.
[ ] Nordhaus, W. and Chen, X. (2014). A sharper image? estimates of the precision of nighttime lights as a proxy for economic statistics. Journal of Economic Geography,15(1):217–246
[ ] Roman, M. et al (2018). Nasas black marble nighttime lights product suite. Remote Sensing of Environment, 210:113–143.
[ ] Stokes, E. C. and Rom´an, M. O. (2022). Tracking covid-19 urban activity changes in the middle east from nighttime lights. Scientific reports, 12(1):8096.
[ ] Sutton, P. C., D Elvidge, C., and Ghosh, T. (2007). A scale-adjusted measure of “urban sprawl” using nighttime satellite imagery. Remote Sensing of Environment, 86(3):353-369
[ ] Luis R. Martinez (2018) - How Much Should We Trust the Dictator’s GDP Estimates?

janbeering commented 1 month ago

Mobility and Economic Activity:

[ ] Fingleton, B. and Szumilo, N. (2019). Simulating the impact of transport infrastructure investment on wages: a dynamic spatial panel model approach. Regional Science and Urban Economics, 75:148–164.
[x] Abramowicz (2024) - Impact of Crisis on Maritime Traffic
[x] Fridström (2023) - Road traffic intensity of GDP
[x] Li (2020) - Estimation of regional economic activity
[ ] Pappalardo - Mobility Data on Well-being
[ ] Putra Arini () -
[ ] Zhou (2019) - Computational Socioeconomics
[ ] Beyzatlar (2014) - Granger-causality between transportation and GDP
[ ] Levinson (2015) - Mutual causality in road network growth and economic development
[ ] Kahn (2013) - China's bullet trains facilitate market integration and mitigate the cost of megacity growth

janbeering commented 1 month ago

Corruption and Reliabilty of Public Data in Ukraine:

[ ] OECD (2022) - Anti Corruption Reforms in Ukraine
[ ] OECD (2021) - Anti-Corruption Review of the Energy Sector in Ukraine
[ ] https://www.worldeconomics.com/
[ ] ILO (2018) - Undeclared Work in Ukraine: Nature, Scope and Measures to Tackle It
[ ] Schneider Collins (2016) - Measuring the Global Shadow Economy
[ ] Bielova (2019) - Labor market- problematic aspects of informal employment in Ukraine
[ ] Williams (2011) - Explaining the Normality of Informal Employment in Ukraine- A Product of Exit or Exclusion?
[ ] Prykhodko (2020) - Adaptation of international recommendations on informal employment in Ukraine
[ ] Williams () - Evaluation of the Existence of Blat
[ ] Yuryk (2020) - INFORMAL EMPLOYMENT IN UKRAINE AND FORMATION OF INSTITUTIONAL CONDITIONS OF ITS MINIMIZATION
[ ] Khodshayan () - TRENDS OF FUNCTIONING OF THE INFORMAL SECTOR OF THE UKRAINE ECONOMY
[ ] Kolomoiets (2021) - Influence of shadow economy legalization on national security of Ukraine

janbeering commented 1 month ago

Econometrics:

[ ] Bartlett, P. L., Long, P. M., Lugosi, G., and Tsigler, A. (2020). Benign overfitting in linear regression. Proceedings of the National Academy of Sciences, 117(48):30063–30070.
[ ] Pesaran, M. H. and Timmermann, A. (1995). Predictability of stock returns: Robustness and economic significance. The Journal of Finance, 50(4):1201–1228.
[ ] Szumilo, N. (2021). Prices of peers: Identifying endogenous price effects in the housing market. The Economic Journal, 131(639):3041–3070.

janbeering commented 1 month ago

Nowcasting GDP: Allgemein:

[ ] Bok, B., Caratelli, D., Giannone, D., Sbordone, A. M., and Tambalotti, A. (2018). Macroeconomic nowcasting and forecasting with big data. Annual Review of Economics, 10:615–643
[ ] Chetty, R., Friedman, J., Hendren, N., Stepner, M., and Team, T. (2020). The economic impacts of covid-19: Evidence from a new public database built using private sector data.
[ ] Ghysels, E. (2016). Macroeconomics and the reality of mixed frequency data. Journal of Econometrics, 193(2):294–314.
[ ] Mazzi, G. L., Mitchell, J., and Montana, G. (2014). Density nowcasts and model combination: Nowcasting euro-area gdp growth over the 2008–09 recession. Oxford Bulletin of Economics and Statistics, 76(2):233–256.
[ ] Proietti, T., Giovannelli, A., Ricchi, O., Citton, A., Tegami, C., and Tinti, C. (2021). Nowcasting gdp and its components in a data-rich environment: The merits of the indirect approach. International Journal of Forecasting, 37(4):1376–1398.
[ ] Stock, J. H. and Watson, M. W. (2002). Forecasting using principal components from a large number of predictors. Journal of the American Statistical Association, 97(460):1167
[ ] Zhou (2019) - Computational Socioeconomics

janbeering commented 1 month ago

Nowcasting GDP Google & Twitter Searches:

[ ] Askitas, N. and Zimmermann, K. F. (2009). Google econometrics and unemployment forecasting.
[ ] Bok´anyi, E., L´abszki, Z., and Vattay, G. (2017). Prediction of employment and unemployment rates from twitter daily rhythms in the US. EPJ Data Science, 6(1).
[ ] Choi, H. and Varian, H. (2009). Predicting the present with google trends. Economic Record, 88:2–9.
[ ] Ettredge, M., Gerdes, J., and Karuga, G. (2005). Using web-based search data to predict macroeconomic statistics. Communications of the ACM, 48(11):87–92.
[ ] G¨otz, T. and Knetsch, T. (2019). Google data in bridge equation models for german gdp. International Journal of Forecasting, 35(1):45–66.
[ ] Indaco, A. (2020). From twitter to gdp: Estimating economic activity from social media. Regional Science and Urban Economics, 85:103591.
[ ] Llorente, A., Garcia-Herranz, M., Cebrian, M., and Moro, E. (2015). Social media fingerprints of unemployment. PLOS ONE, 10(5):e0128692.
[ ] Mclaren, N. and Shanbhogue, R. (2011). Using internet search data as economic indicators. SSRN Electronic Journal, 2:134–140.
[ ] Ortega-Bastida, J., Gallego, A. J., Rico-Juan, J. R., and Albarr´an, P. (2021). A multimodal approach for regional GDP prediction using social media activity and historical information. Applied Soft Computing, 111:107693.
[ ] Woloszko, N. (2020). Tracking activity in real time with google trends. OECD Economics, (1634).
[ ] Woo, J. and Owen, A. L. (2019). Forecasting private consumption with google trends data. Journal of Forecasting, 38(2):81–91.

janbeering commented 1 week ago

Ukrainian Economy:

[ ] Lutsik et al - Prediction of possible scenarios for the development of the Ukrainian economy in the context of a “hybrid” war the Russian Federation. https://paperssds.eu/index.php/JSPSDS/article/view/185

janbeering commented 1 week ago

Vehicle Detection, Satelite Imagery, Technicalities:

[x] Stupara (2020) - Vehicle Detection in Overhead Satellite Images Using
[x] https://gist.github.com/arthurdouillard
[x] https://medium.com/data-from-the-trenches/object-detection-with-deep-learning-on-aerial-imagery-2465078db8a9
[ ] Riantini Virtriana et al. - Machine learning remote sensing using the random forest classifier to detect the building damage caused by the Anak Krakatau Volcano tsunami
[ ] Brooke Simmons, Chris Lintott, Steven Reece, et al. - Disaster, Infrastructure and Participatory Knowledge The Planetary Response Network
[ ] Ana Andries, Stephen Morse, Richard J. Murphy, Jim Lynch, and Emma R. Woolliams - Using Data from Earth Observation to Support Sustainable Development Indicators: An Analysis of the Literature and Challenges for the Future

janbeering / MA

Reading List #1