This paper distills and identifies global liquidity (GL) momenta from the macro-financial data of advanced economies through a factor model with sign restrictions as policy-driven, market-driven, and risk averseness factors. Using a panel factor-augmented VAR, we investigate responses of emerging market economies (EMEs) to GL shocks. A policy-driven liquidity increase boosts growth in EMEs, elevating stock prices and currency values, while a risk averseness rise has an opposite effect. A market-driven GL expansion boosts stock markets and lowers funding costs, increasing competitiveness and current account. Inflation targeting EMEs fare better than EMEs under alternative regimes with respect to macrofinancial volatility.
This paper distills and identifies global liquidity (GL) momenta from the macro-financial data of advanced economies through a factor model with sign restrictions as policy-driven, market-driven, and risk averseness factors. Using a panel factor-augmented VAR, we investigate responses of emerging market economies (EMEs) to GL shocks. A policy-driven liquidity increase boosts growth in EMEs, elevating stock prices and currency values, while a risk averseness rise has an opposite effect. A market-driven GL expansion boosts stock markets and lowers funding costs, increasing competitiveness and current account. Inflation targeting EMEs fare better than EMEs under alternative regimes with respect to macrofinancial volatility.
We assess the effect of tighter monetary policy in the U.S. and emerging market economies (EMEs) on EMEs using a panel factor-augmented VAR model. We find that a U.S. policy rate hike outstrips an equivalent domestic rate hike in its impacts on EMEs. In addition, EMEs show divergent policy responses and their macro-financial responses differ depending upon their economic fundamentals in the face of tighter U.S. policy. In particular, we find that high-inflation than low-inflation EMEs are more susceptible to the shock stemming from a U.S. federal funds rate hike.
This paper distills and identifies global liquidity (GL) momenta from the macro-financial data of advanced economies through a factor model with sign restrictions as policy-driven, market-driven, and risk averseness factors. Using a panel factor-augmented VAR, we investigate responses of emerging market economies (EMEs) to GL shocks. A policy-driven liquidity increase boosts growth in EMEs, elevating stock prices and currency values, while a risk averseness rise has an opposite effect. A market-driven GL expansion boosts stock markets and lowers funding costs, increasing competitiveness and current account. Inflation targeting EMEs fare better than EMEs under alternative regimes with respect to macrofinancial volatility.
This paper deals with the input-output modeling of a vector controlled PMSM drive system and design of a simple multiple model adaptive control (MMAC) scheme with desired transient responses. We present a discrete-time modeling technique using closed-loop identification that can experimentally identify the equivalent models in the d-q coordinates. A bank of linear models for the equivalent plant of the current loop is first obtained by identifying them at several operating points of the current to account for nonlinearity. Based on these models, we suggest a simple q-axis MMAC combined with a fixed d-axis controller. After the current controller is designed, another equivalent model including the current controller in the speed control loop shall be similarly obtained, and then a fixed speed controller is synthesized. The proposed approach is demonstrated by experiments. The experimental set up consists of a surface mounted PMSM (5 KW, 220V, 8 poles) equipped with a flywheel load of 220kg and a digital controller using DSP (TMS320F28335).
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