1{"text": "{\"genre\":\"empirical\",\"subfield\":\"financial_intermediation_banking\",\"subfield_secondary\":\"law and finance / corporate credit\",\"primary_method\":\"reduced_form_regression\",\"identification\":{\"estimand\":\"Effect of a lender's accumulated past bad loans on the probability that the same borrower delays repayment to that lender, and how this effect varies with local judicial (collateral-recovery) efficiency\",\"strategy\":\"Linear probability model on bank-firm-quarter Credit Register data. Firm-quarter fixed effects absorb borrower fundamentals, so variation comes from differences across a multi-bank firm's lenders. Bad loans are interacted with court-level duration of property execution proceedings. 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Regression tables follow, with OLS and IV columns side by side. Notes define variables by reference to Appendix A. Standard errors are in parentheses, clustered at the bank level, with significance stars.\",\"units_stated_in_notes\":true,\"standard_errors_description\":\"clustered\"},\"figures\":{\"uncertainty_shown\":\"unclear\"},\"conclusion\":{\"bounded_claims\":true,\"policy_implications\":true,\"open_questions\":false,\"restates_contribution\":true},\"hedging\":{\"level\":\"moderate\",\"typical_devices\":[\"results suggest\",\"it seems likely\",\"might impair\",\"qualitatively similar\"]},\"claim_evidence\":[{\"claim\":\"Lenders' past bad loans raise the probability that borrowers delay repayment to them\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table V\"},{\"claim\":\"The effect of bad loans on delays grows with slower collateral enforcement and is insignificant where courts are efficient\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table VI; Figure 3\"},{\"claim\":\"In top-quartile legal inefficiency areas, a 1-SD rise in past bad loans raises delays by about 50% of the mean\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table VI\"},{\"claim\":\"Late repayments reduce lender profitability\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table VII\"},{\"claim\":\"Even safe borrowers selectively delay payment to weak banks where enforcement is poor\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table VIII; Figures 4-5\"},{\"claim\":\"Firm-level total delays rise with exposure to weak lenders, more so under weak enforcement\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table IX; Figure 6\"},{\"claim\":\"Results are robust to first delays, loan terms, same-jurisdiction pairs, matching, culture and governance\",\"evidence_type\":\"table\",\"evidence_ref\":\"Table X; Table B2\"},{\"claim\":\"Italian bad loans were large and concentrated in nonfinancial business lending\",\"evidence_type\":\"descriptive_statistic\",\"evidence_ref\":\"Introduction, Bank of Italy (2016)\"}],\"structural_summary\":\"The paper opens with the aggregate nonperforming-loan problem in Italy, states the headline finding with a magnitude, and explains identification via firm-quarter effects in multi-bank relationships. It then previews the IV defense against reverse causality and frames a strategic-versus-selective delay question with policy implications. A separate literature section positions the work against theories of repayment unraveling. A data section combines four registers. A long empirical section covers baseline, judicial-interaction, profit, borrower-risk and firm-level analyses, with embedded robustness subsections. A short conclusion claims priority and draws implications for legal enforcement and transparency.\",\"writing_profile_keywords\":[\"credit register\",\"firm-time fixed effects\",\"multiple bank relationships\",\"judicial efficiency interaction\",\"shift-share instrument\",\"marginal effect plots\",\"strategic default\",\"law and finance\"],\"confidence\":0.82,\"notes\":\"Section 3 is labeled empirical design by rule but mostly contains results; it is classified as results here. No explicit roadmap is visible in the truncated introduction. 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