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International Monetary Fund. European Dept.
This Selected Issues paper on the Republic of Poland constructs a financial conditions index for Poland to explore the link between financial conditions and real economic activity. Measures to contain the fiscal deficit in the aftermath of the global financial crisis led to a reduction in the headline deficit from 7.9 percent of GDP in 2010 to 3.9 percent in 2012. The authorities plan to implement a permanent fiscal rule. This would complement existing public debt limits, which have proven useful but insufficient in the past. Regarding mechanism design, the authorities have expressed their preference for a simple expenditure rule, on grounds of transparency, predictability, and ease of implementation across budgetary units.
Giang Ho and Miss Yinqiu Lu
This paper constructs a financial conditions index for Poland to explore the link between financial conditions and real economic activity. The index in constructed by applying two complementary approaches—factor analysis and vector auto-regression approach. We evaluate the index’s forecasting performance against a composite leading indicator developed by the OECD. We found that the FCI is highly correlated with GDP growth, attesting to the importance of financial sector in Poland’s economy. In-sample and out-of-sample forecasting exercises indicate that the FCI can outperform the CLI in predicting near-term GDP growth.
International Monetary Fund. European Dept.
This Selected Issues paper examines the vulnerability of firms in Malta and investigates the effect of their balance sheets on investment in innovation. The results indicate that, while the financial health of medium and large firms has improved in recent years, vulnerabilities remain in the construction sector and for small and medium enterprises. Firms with weaker balance sheets tend to invest less in innovation, even during good times. Policy implications call for (1) accelerating the restructuring of corporate balance sheets of highly leveraged but viable firms, (2) improving the insolvency framework to allow a fast exit of nonviable companies, and (3) expanding corporate funding options for small and medium enterprises, including via nonbank financing alternatives.
International Monetary Fund. African Dept.
This Selected Issues paper develops a Financial Conditions Index (FCI) for Mauritius—an instrument to gauge the operational state of the financial sector and predict real economy activity. The evolution of Mauritius’ financial services sector has been supported by a vibrant offshore corporate sector. Given the strong macro-financial linkages, it is imperative to closely monitor domestic financial developments. Financial developments are broader than monetary developments depicting money supply and interest rates. The FCI is a robust predictor of real GDP growth in Mauritius. The FCI can also help inform macroprudential policy decisions. Decisions on setting the countercyclical capital buffer of Basel III could be informed by analyzing developments in the FCI. As historically Mauritius has not experienced drastic swings in financial credit, testing the constructed FCIs for predicting boom-bust episodes is difficult. Nevertheless, the FCI signaled lax financial conditions in 2009 and again in 2012 that likely contributed to accelerated credit growth in 2012–2013 and a subsequent acceleration in nonperforming loans during 2014–2016.
Giang Ho and Miss Yinqiu Lu

Front Matter Page European Department Contents I. Introduction II. Overview of Methodology A. Vector Auto-Regression B. Factor Analysis III. A Financicial Conditions Index for Poland A. Overview of the Constructed FCIs B. VAR-Based FCI C. Factor-Based FCI IV. Forecast Evaluation V. Conclusion References Tables I. Correlations Between Financial Variables and Real Activity, 2004Q1–2012Q4 II. In-Sample Predictive Tests III. Out-of-Sample Predictive Tests, Relative RMSE Figure I. Contributions to FCI, 2004Q1–2013Q

International Monetary Fund. African Dept.

FIGURES 1. PCA FCIs Factor Loadings 2. Constructed FCIs and GDP Growth, 2003Q2–2018Q3 3. FCI, Credit Gap and Credit Booms and Busts, 2003Q2–2018Q4 4. FCI, Credit Gap, Loan Quality and Banks’ Profitability, 2003Q2–2018Q4 TABLES 1. Correlations Between FCIs and Real Activity, 2003Q2–2018Q3 2. Root Mean Squared Errors References

International Monetary Fund. African Dept.

-of-sample tests generally show good predictive power of FCIs, and they are increasingly being used as a tool for in-house forecasting by policymaking institutions. The IMF, e.g., has been using FCIs among other inputs to project the “growth-at-risk”—both at the global level ( IMF, 2017 ; IMF, 2018a ), and for individual countries (e.g. IMF, 2018b ). 4. Two approaches stand out in constructing FCIs . First, the weighted-sum approach, based on vector autoregressive (VAR) models, obtains the weights of the individual financial variables in the FCI from the cumulative impulse