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Big Data Information and Nowcasting: Consumption and Investment from Bank Transactions in Turkey

Ali B. Barlas, Seda Guler Mert, Berk Orkun Isa, Alvaro Ortiz, Tomasa Rodrigo, Baris Soybilgen, Ege Yazgan

arXiv 5 Jul 2021 · Econometrics · 1 citations (OpenAlex)

arXiv:2107.03299 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We use the aggregate information from individual-to-firm and firm-to-firm in Garanti BBVA Bank transactions to mimic domestic private demand. Particularly, we replicate the quarterly national accounts aggregate consumption and investment (gross fixed capital formation) and its bigger components (Machinery and Equipment and Construction) in real time for the case of Turkey. In order to validate the usefulness of the information derived from these indicators we test the nowcasting ability of both indicators to nowcast the Turkish GDP using different nowcasting models. The results are successful and confirm the usefulness of Consumption and Investment Banking transactions for nowcasting purposes. The value of the Big data information is more relevant at the beginning of the nowcasting process, when the traditional hard data information is scarce. This makes this information specially relevant for those countries where statistical release lags are longer like the Emerging Markets.

Citation extraction

44
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in-text mentions
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distinct cited
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appendix boundary found by appendix_titled_section at “Appendix” · 99% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Barlas, A. B., S. Güler, A. Ortiz, and T. Rodrigo (2020) Investment in real time and High definition: A Big data Approach self0.81142100%
2Carvalho, V. M., S. Hansen, A. Ortiz, J. R. Garcia, T. Rodrigo, S. R… (2020) Tracking the covid-19 crisis with high resolution transaction data0.73732100%
3Chetty, R., J. Friedman, N. Hendren, M. Stepner, and T. O. I. Team (2020) How did covid-19 and stabilization policies affect spending and employment? a new real-time economic tracker based on private se…0.73732100%
4Andersen, A. L., E. T. Hansen, N. Johannesen, and A. Sheridan (2020) Consumer responses to the covid-19 crisis: Evidence from bank account transaction data0.64422100%
5Ankargren, S. and Y. Yang (2019) Mixed-frequency bayesian var models in r: the mfbvar package0.58531100%
Hansenunmatched citation key Hansen0.58531100%
7Soybilgen, B. and E. Yazgan (2021) Nowcasting us gdp using tree-based ensemble models and dynamic factors self0.58531100%
Bakerunmatched citation key Baker0.51121100%
9Bańbura, M. and M. Modugno (2014) Maximum Likelihood Estimation of Factor Models on Datasets with Arbitrary Pattern of Missing Data0.51121100%
Carvalhounmatched citation key Carvalho0.51121100%

Showing the top 10 of 132 scored citations. 3 of these could not be matched to a bibliography entry, so only the citation key is shown.