Bibliographic record
Abstract
In the last decade, there has been a newfound interest within economics in culture, its effects on economic outcomes, and its historical determinants. Although significant progress has been made, there are still many large questions that remain unanswered. My dissertation addresses two of those, namely the effect of history on current levels of trust in political institutions and the twofold relationship between culture and economic outcomes. My first chapter examines the effect of historical changes in political borders on current citizens' levels of trust in political institutions. Political trust also depends on current political institutions, so that a straightforward cross-country analysis would not be able to disentangle the effect of history from the effect of institutions. To address this problem, I compare regions that are part of the same country today and therefore share the same political institutions, but have had a different number of border changes in the past. I study six countries that have such within-country variation in border changes--Slovenia, Croatia, Serbia, Montenegro, Romania and Ukraine. Using data for five hundred years of border changes and three contemporary household-level surveys, I show that more frequent border changes in the past lead to lower current trust in political institutions. The estimated effect is large: border changes can explain 45% of the observed average difference in household-level political trust between the countries studied in my paper and the UK, which has enjoyed stable borders. The second chapter examines immigrants' socio-economic outcomes. I use the variation in cultural distance between immigrants' birth and host countries to estimate the cost of adapting to a new cultural milieu. Using individual level data on immigrants from Europe, Canada and the US, I find that a increase of one standard deviation in the cultural distance between an immigrant's birth and host countries decreases the immigrant's expected earnings by 7.2% and has negative effect on numerous immigrants' social outcomes as well. As predicted by my model, the effect of cultural distance is the strongest for immigrants who arrived recently, and who immigrated at an older age.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".