Global financial shocks and inflationary dynamics in Kazakhstan

This paper revisits the international finance trilemma by analyzing how different monetary policy objectives and exchange rate regimes shape the transmission of global risk shocks. Using a structural vector autoregressive model with exogenous variables (SVARX), we examine the monetary policy responses and exchange rate fluctuations of ASEAN+4 economies—China, Japan, Korea, and Hong Kong—to external shocks including U.S. monetary policy changes, oil price fluctuations, global policy uncertainty, and financial risk during 2010–2022. Economies are grouped according to their trilemma configurations: floating exchange rates with free capital flows, fixed exchange rates, and capital control regimes. Our findings broadly support the trilemma hypothesis: fixed-rate economies align with U.S. interest rate movements, capital control economies retain greater monetary autonomy, and open, floating regimes show partial responsiveness. More importantly, monetary responses vary by global shock type: U.S. monetary policy drives the most synchronized policy reactions, while oil price and uncertainty shocks produce more heterogeneous outcomes. Robustness checks include alternative model specifications, where global shocks are treated as endogenous, and extensions, such as using Japan’s monetary base as a proxy for unconventional monetary policy. These results refine the empirical understanding of the trilemma by showing that its dynamics depend not only on institutional arrangements but also on the nature of global shocks—underscoring the need for more tailored and, where possible, regionally coordinated monetary policy strategies.

The run-up in oil prices after 2004 coincided with a growing flow of investment to commodity markets and an increased price comovement between different commodities. We analyze whether speculation in the oil market played a key role in driving this salient empirical pattern. We identify oil shocks from a large dataset using a factor-augmented autoregressive (FAVAR) model. We analyze the role of speculation in comparison to supply and demand forces as drivers of oil prices. The main results are as follows: (i) While global demand shocks account for the largest share of oil price fluctuations, financial speculative demand shocks are the second most important driver. (ii) The comovement between oil prices and the price of other commodities is explained by global demand and financial speculative demand shocks. (iii) The increase in oil prices in the last decade is mainly explained by the strength of global demand. However, financial speculation played a significant role in the oil price increase between 2004 and 2008, and its subsequent collapse. Our results support the view that the financialization process of commodity markets explains part of the recent increase in oil prices.

This study examined the determinants of exchange rate volatility basing evidence on 7 African countries; Niger, Sudan, Cameron, Equatorial Guinea, Tunisia, Congo, and Cote D’Ivoire from 1990-2023. The study conducted the Autoregressive Distributive Lag (ARDL) bounds testing for co-integration and also estimated the error correction model. Furthermore, ARCH and GARCH models were analyzed to measure the volatility of a time series by fitting an autoregressive model to the squared residuals of the time series. The ARCH and GARCH results suggest the volatility of the exchange rate markets in the aforementioned countries is not random. The speed of adjustment of the volatility in the exchange rate of the Sudanese economy is 39%, in Niger Republic it is 50%, in Cameroon it is 52%, in Tunisia it is 55%, in Congo the speed is 32%, in Equatorial Guinea, the speed of adjustment is 58% and in Côte D’Ivoire the speed is 45%, respectively. The study found that the determinants of exchange rate volatility among African countries vary depending on the specific country. The observed volatility in the Sudanese exchange rate was anchored by the significant positive influence of inflation and income differentials as well as the significant negative influence of interest rate differential. In Niger Republic, exchange rate volatility was driven by the significant positive influence of productivity growth and money supply as well as the significant variation in oil prices and interest rate differentials. The observed short-run volatility in Cameroon's exchange rate was significantly and positively influenced by inflation differential and money supply variation whereas it was significantly but negatively propelled by interest rate differential and oil price shock. In Tunisia, exchange rate volatility was stimulated by the significant positive influence of inflation differential, productivity growth, oil price shock, and the significant negative role played by trade balance. The observed short-run volatility in the Congolese exchange rate was induced by the significant positive impact of inflation differential, income differential, trade balance, variation in money supply, and the significant negative impact of interest rate differential. In Equatorial Guinea, the observed exchange rate volatility was determined based on the significant and positive impact of differential in the inflation rate, oil price shock, changes in the money stock, and the foreign balance of trade. The observed volatility in the Côte D’Ivoire exchange rate was significantly and positively driven by the differentials in inflation rate, interest rate, and income level, the foreign trade balance but significantly stimulated by the negative influence of oil price shock. The general policy advice is that governments of all the countries covered by the study should implement exchange rate controls to limit the volatility of their currency fluctuation by imposing a limit on the amount of foreign currency that can be traded in the country. African governments should monitor the inflation differential between their own country and their trading partners to see if it is becoming too large. If it is, the government might raise interest rates to make its currency more attractive to investors.

Foreign or global economic and financial shocks can be significant drivers of economic outcomes in small open economies such as Australia, and are therefore a considerable source of uncertainty to the Australian economic outlook. Examining the extent to which global shocks affect the Australian financial system and economy and the channels through which these shocks operated over the 1990–2019 period, we find that global shocks drive considerable variation in the exchange rate and the cash rate, but a smaller proportion of variation in economic variables like real GDP. This suggests that, over our sample, the exchange rate and domestic monetary policy have effectively buffered the Australian economy from global shocks. Unlike some other recent literature on global spillovers, we do not find the Australian banking system to be a substantial channel of financial and economic spillovers to Australia.

Business cycles are increasingly driven by global shocks, rather than the domestic demand shocks prominent in earlier decades, posing challenges for central banks seeking to meet domestic mandates and communicate their policy decisions. This paper analyzes the evolving influence and characteristics of global and domestic shocks in advanced economies from 1970-2024 using a new FAVAR model that decomposes movements in interest rates, inflation, and output growth into four global shocks (demand, supply, oil, and monetary policy) and three domestic shocks (demand, supply, and monetary policy). We find that the role of global shocks has increased sharply over time and that their characteristics differ from those of domestic shocks across multiple dimensions. Compared to domestic shocks, global shocks have a larger supply component, higher variance, more persistent effects on inflation, and are more asymmetric (contributing more to tightening than to easing phases of monetary policy). As global supply shocks have become more prominent, central banks have also been less willing to "look through" their effects on inflation than for comparable domestic shocks. The distinct characteristics and rising influence of global shocks-particularly global supply shocks-have significant implications for modeling monetary policy and designing central bank frameworks.

Global financial conditions, country spreads and macroeconomic fluctuations in emerging countries

This article studies inflation dynamics and the output–inflation trade‐off in small open economies. We estimate a series of VAR models for a set of six Asian emerging market economies, in which we identify a battery of domestic and global shocks using sign restrictions. We find that global shocks explain large parts of inflation and output dynamics. A series of counterfactuals support these findings and suggest that the role of monetary policy is limited. We estimate reduced‐form Phillips curve regressions based on alternative decompositions of output into global and domestic components. For most countries, we find a positive and significant correlation between inflation and the fraction of GDP driven by domestic shocks only. While including the output component driven by oil prices seems to ‘flatten’ the Phillips curve, though the effect is not significant, the component driven by global demand shocks ‘steepens’ the inflation–output nexus.

This study examines global shocks and the volatility of the Russian rubble/United States dollar exchange rate using the symmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH), and Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) models. The GARCH and APARCH are employed under normal (Normal Gaussian) and non-normal (Student’s t and Generalized Error) distributions. Using monthly exchange rate data covering January 1994 – December 2013, the study finds that the symmetric (GARCH) model has the best fit under the non-normal distribution, which improves the overall estimation for measuring conditional variance. Conversely, the APARCH model does not show asymmetric response in exchange rate volatility and global shocks, resulting in no presence of leverage effect. The GARCH model under the Student’s t distribution produces better fit for estimating exchange rate volatility and global shocks in Russia, compared to the APARCH model. Keywords: exchange rate volatility, global Shocks, GARCH and APARCH models. JEL Classification: F30, F31, P33

The policy of increasing domestic fuel oil, as a consequence of rising world oil prices, has resulted in changing economic conditions, bearing in mind that oil prices and production are wrong macroeconomic assumptions and are included in the State Revenue and Expenditure Budget. This study aims to determine the impact of rising fuel prices and government subsidies on Indonesia's economic performance. The data used in this study are time series data from 2000 to 2022. Data were obtained from the Indonesian Central Bureau of Statistics, the Ministry of Energy and Mineral Resources, the Ministry of Finance, and Bank Indonesia. This study uses an econometric model using a system of simultaneous equations. The research results show that; The main factors that caused the increase in domestic fuel prices, including crude oil prices, gasoline, diesel, kerosene and aviation fuel, were the increase in world oil prices and the previous year's oil prices. The estimation results also show that the increase in gasoline and diesel fuel can increase the number of poor people, unemployment and inflation in Indonesia. The policy simulation results show that the increase in oil prices has a significant impact on increasing the number of poor people, increasing unemployment and inflation, if this increase is not followed by subsidies in the form of non-energy.

In this study, we estimate the contribution of global demand, supply and commodity shocks to the dynamics of Russian macroeconomic variables. The main tool used in this work is a factor augmented vector autoregression (FAVAR) that allows extracting global factors from a wide range of variables. Recursive and sign restrictions are used to identify global shocks. Russian economy is represented by a large set of informational series aggregated into a small number of factors. FAVAR approach allows for extended inference on the reaction of Russian macroeconomic variables to global shocks. Impulse response function analysis shows that Russian economy is affected by all three specifi ed global shocks and forecast error decompositions indicate that those shocks account for nearly 80 per cent of key variables dynamics. We also showed that global demand and global commodity shocks were more crucial compared to the third type of shocks in explaining macroeconomic dynamics.

This paper uses a panel structural vector autoregressive (VAR) model to investigate the extent to which global financial conditions, i.e., a global risk-free interest rate and global financial risk, and country spreads contribute to macroeconomic fluctuations in emerging countries. The main findings are: (1) Global financial risk shocks explain about 20 percent of movements both in the country spread and in the aggregate activity in emerging economies. (2) The contribution of global risk-free interest rate shocks to macroeconomic fluctuations in emerging economies is negligible. Its role, which was emphasized in the literature, is taken up by global financial risk shocks. (3) Country spread shocks explain about 15 percent of the business cycles in emerging economies. (4) Interdependence between economic activity and the country spread is a key mechanism through which global financial shocks are transmitted to emerging economies.

This paper uses a panel structural vector autoregressive (VAR) model to investigate the extent to which global financial conditions, i.e., a global risk-free interest rate and global financial risk, and country spreads contribute to macroeconomic fluctuations in emerging countries. The main findings are: (1) Global financial risk shocks explain about 20 percent of movements both in the country spread and in the aggregate activity in emerging economies. (2) The contribution of global risk-free interest rate shocks to macroeconomic fluctuations in emerging economies is negligible. Its role, which was emphasized in the literature, is taken up by global financial risk shocks. (3) Country spread shocks explain about 15 percent of the business cycles in emerging economies. (4) Interdependence between economic activity and the country spread is a key mechanism through which global financial shocks are transmitted to emerging economies.

Global financial shocks and foreign asset repatriation: Do local investors play a stabilizing role?

Exchange rate pass-through in emerging Asia and exposure to external shocks

This paper sought to shed light on the impact of shocks to global oil prices on the Leone/US Dollar exchange rate in Sierra Leone during the post war period spanning 2002M6 to 2020M5. To achieve this, the paper employed the GARCH family models with structural breaks. After establishing the existence of ARCH effects and ensuring stationarity of the data set, the paper first applied both GARCH (1, 1) and GARCH (1, 1) in Mean models to capture the symmetry effect of global oil prices increase on exchange rate. Furthermore, the paper employed exponential GARCH (EGARCH (1, 1)) model to capture the asymmetric impact of oil price increase on the Leone/US Dollar exchange rate. Among the three models estimated, the EGARCH (1, 1) model was found to have the best fit as all of its mean and variance coefficients were not only found to be statistically significant but also had the least values of the model selection criteria. The empirical results suggest that an increase in oil price leads to depreciation of the exchanges rate in Sierra Leone and that exchange rate volatility exhibits persistence and autoregressive behavior. Furthermore, the paper finds evidence of asymmetry, indicating that positive shocks to crude oil prices will lead to a higher volatility in the exchange rate than negative shocks of the same magnitude. Finally, the paper finds evidence of structural breaks in the exchange series. The main policy implication from these findings is that the monetary authority should consider global oil price dynamics and the past history of exchange rate movements when formulating policy responses to exchange rate volatility in Sierra Leone.