دانلود مقاله تأثیر اقتصاد کلان بر ریسک اعتباری پرتفولیوی بانک
خلاصه
1. مقدمه
2. سیستم مالی کلمبیا
3. روش شناسی
4. برآوردها و نتایج
5. نتیجه گیری ها
یادداشت
بیانیه افشا
منابع
Abstract
1. Introduction
2. The Colombian Financial System
3. Methodology
4. Estimates and Results
5. Conclusions
Notes
Disclosure Statement
References
چکیده
این مقاله عوامل تعیین کننده ریسک اعتباری را برای اقتصاد کلمبیا، یک اقتصاد کوچک در حال ظهور در آمریکای لاتین بررسی می کند. با استفاده از نمونه ای از 28 بانک بزرگ در دوره 2009-2019 و رویکرد پانل داده پویا، متوجه می شویم که وخامت محیط اقتصاد کلان بر ادراک ریسک اعتباری بانک ها که از طریق وام های غیرجاری و ذخایر زیان وام اندازه گیری می شود، تأثیر می گذارد. از سوی دیگر، فضای سیاسی بهتری که با توافق‌های صلح ایجاد شد، چنین تأثیری را هموار کرد. برآوردها نشان‌دهنده واکنش‌های متفاوت هنگام تشخیص نوع وام است. اعتبار تجاری به شدت به بیکاری بستگی دارد، در حالی که ریسک اعتباری مصرف کننده به نرخ بهره حساس تر است. در مورد وام های رهنی، رشد اقتصادی و نرخ بیکاری حیاتی ترین متغیرها برای کاهش ریسک هستند. این نتایج تأثیر محیط اقتصادی بر خطوط اعتباری با ویژگی‌های متفاوت را روشن می‌کند.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
This paper explores the determinants of credit risk for the Colombian economy, a small emerging economy in Latin American. Using a sample of 28 large banks over the 2009–2019 period and the dynamic data panel approach, we find that the macroeconomic environment’s deterioration affects the credit risk perception held by banks as measured through non-performing loans and loan loss provisions. On the other hand, a better political environment brought about by peace accords smoothed such an impact. Estimates indicate different reactions when distinguishing by loan type. Business credit depends heavily on unemployment, while consumer credit risk is more sensitive to the interest rate. In the case of mortgage loans, economic growth and the unemployment rate are the most critical variables to mitigate risk. These results shed light on the impact of the economic environment on credit lines with different features.
Introduction
The current economic recession caused by the COVID-19 pandemic has drawn attention to the consequences it may have on the banking system. As a result, there is great interest in knowing which indicators can provide efficient signals about financial instability (Chau, Lin, and Lin 2020). Loan performance is an essential channel to analyze the effect that macroeconomic factors have on banking crises. Unfavorable economic conditions such as lower economic growth and high unemployment can increase loan defaults and bankruptcies, so the issue of the procyclicality of the financial system should attract the attention of both academics and policymakers because it can exacerbate the economic downturn (Castro 2013: Cecchetti and Kohler 2014; De Moraes and De Mendonça 2019).
Credit risk is the main channel for relating economic shocks to bank balance sheets. It is defined as the risk that a loan will not be paid (partially or totally) to the lender and it is a problem that has received extensive theoretical research. The seminal paper of Altman and Saunders (1998) initially surveyed the approaches that existed on the subject. Credit risk analyses have changed from so-called banking expert systems analyses to more objective schemes. Until the late 1980s, bankers used microeconomic information on the borrower such as reputation, capital, ability to pay, and collaterals to make subjective judgments about credit risk. By the late 1990s, these models began to fail because they did not consider the economic environment in which banks operate. New approaches began to explore alternatives to explain credit risk based on the possible states of the economy. In particular, the study by Salas and Saurina (2002) pioneered this issue by combining micro and macroeconomic data to assess credit risk.
Conclusions
The global economic crisis is paying attention to the problems it can bring to the financial system. In this sense, this study analyzed the effect of macroeconomic perspectives on credit risk for the Colombian case. Through a dynamic data panel approach for the period 2009–2019, it was found that the macroeconomic environment is the primary determinant of Colombia’s credit risk. Credit risk increases with declines in GDP growth, rising unemployment, and tightening monetary policy rates.
In 2020 the Colombian economy entered a severe recession and, according to the results of this study, credit risk is likely to increase. In terms of economic policy, this means a threat to financial stability and the possibility of a credit crunch (Louzis, Vouldis, and Metaxas 2012), so different incentives for each type of loan are needed to recover the financial system. Government endorsements and mortgage subsidy policies can help mitigate financial market failures.