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on International Finance |
| By: | Arisa Chantaraboontha |
| Abstract: | This paper examines the responses of foreign exchange rates to the Federal Reserve’s large-scale asset purchases (LSAPs) and forward guidance (FWG) from 2009 to 2022 using local projections. I confirm heterogeneous responses of examined foreign exchange rates to unconventional shocks, varying by magnitude, direction, and duration depending on monetary policy conditions and the type of shock. Both shocks caused the appreciation of foreign exchange rates against the US Dollar in all monetary policy cycles, except for the FWG shock during normalization periods of monetary policy. The FWG shock had a greater impact magnitude on the examined foreign exchange rates than the LSAPs shock. The effects of both unconventional shocks were more persistent during periods of zero lower bound (ZLB) on the policy interest rate than during normalization periods of monetary policy. However, the impact of such shocks on foreign exchange rates diminished within a couple of months, contrasting with the literature that finds more persistent effects. The implementation of variance decomposition reveals that the FWG shock had a significantly greater influence on foreign exchange rate variation than the LSAPs shock, emphasizing the importance of effective guidance communication to the markets. |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:dpr:wpaper:1276 |
| By: | Arno Botha; Tanja Verster; Roland Breedt |
| Abstract: | The lifetime behaviour of loans is notoriously difficult to model, which can compromise a bank's financial reserves against future losses, if modelled poorly. Therefore, we present a data-driven comparative study amongst three techniques in modelling a series of default risk estimates over the lifetime of each loan, i.e., its term-structure. The behaviour of loans can be described using a nonstationary and time-dependent semi-Markov model, though we model its elements using a multistate regression-based approach. As such, the transition probabilities are explicitly modelled as a function of a rich set of input variables, including macroeconomic and loan-level inputs. Our modelling techniques are deliberately chosen in ascending order of complexity: 1) a Markov chain; 2) beta regression; and 3) multinomial logistic regression. Using residential mortgage data, our results show that each successive model outperforms the previous, likely as a result of greater sophistication. This finding required devising a novel suite of simple model diagnostics, which can itself be reused in assessing sampling representativeness and the performance of other modelling techniques. These contributions surely advance the current practice within banking when conducting multistate modelling. Consequently, we believe that the estimation of loss reserves will be more timeous and accurate under IFRS 9. |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2502.14479 |
| By: | Owen Nie; Nepomuk Dunz; Hector Pollitt |
| Keywords: | Finance and Financial Sector Development-Banks & Banking Reform |
| Date: | 2024–07 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wboper:41970 |
| By: | David Lee Kuo Chuen; Yang Li |
| Abstract: | Blockchain technology, though conceptualized in the early 1990s, only gained practical relevance with Bitcoin's launch in 2009. Recent advancements have demonstrated its transformative potential, particularly in the digital art and global payment sectors. Non-fungible tokens (NFTs) have redefined digital ownership, while financial institutions use blockchain to enhance cross-border transactions, reducing costs and settlement times. Using the Diamond-Mortensen-Pissarides (DMP) model, this paper examines blockchain's impact on labor markets by improving job-matching efficiency, thereby reducing unemployment. However, high research costs and competition with incumbent technologies hinder early-stage blockchain adoption. We extend the DMP model to analyze the role of government intervention through tax and wage policies in mitigating these barriers. Our findings suggest that lowering firm tax rates can accelerate blockchain innovation, enhance labor market efficiency, and promote employment growth, highlighting the critical balance between technological progress and economic policy in fostering blockchain-driven economic transformation. |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2502.15549 |
| By: | Annika Camehl (Erasmus University Rotterdam); Tomasz Wo\'zniak (University of Melbourne) |
| Abstract: | We propose a novel Bayesian heteroskedastic Markov-switching structural vector autoregression with data-driven time-varying identification. The model selects among alternative patterns of exclusion restrictions to identify structural shocks within the Markov process regimes. We implement the selection through a multinomial prior distribution over these patterns, which is a spike'n'slab prior for individual parameters. By combining a Markov-switching structural matrix with heteroskedastic structural shocks following a stochastic volatility process, the model enables shock identification through time-varying volatility within a regime. As a result, the exclusion restrictions become over-identifying, and their selection is driven by the signal from the data. Our empirical application shows that data support time variation in the US monetary policy shock identification. We also verify that time-varying volatility identifies the monetary policy shock within the regimes. |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:arx:papers:2502.19659 |