Regime-based Approach Research Articles

Technological catch-up in the Iranian steel industry: Integrating regime-based and complex product systems approaches

Researchers in the technological catch-up field have recently directed their attention toward a regime-based approach and Complex Product Systems (CoPs) streams. Within this context, studies on each stream demonstrate how industry-specific frameworks in developing countries influence technological catch-up dynamics. This study explores these dynamics by analyzing market and technological regimes within Iran's steel industry as semi-CoPs, comprehensively. The study utilizes historical and content analyses to delineate five capability-building waves and extract themes and dimensions from documents and expert interviews conducted within the steel industry. The findings show that Iran's steel industry catch-up strategy is based on a path-following in which synthesizing overseas technology transfer with indigenous technological developments occurs. That is, firms enrich their indigenous capabilities through reverse engineering of established technologies like MIDREX, progressing to re-engineering existing technologies in iron-making. The enhancement of capabilities, coupled with the employment of opportunity windows, has paved the way for the path-creation in minor technology that has ultimately resulted in the advent of PERED technology. Finally, the findings are further compared with other domestic industries and insights are sought from international counterparts for researchers and participators.

Uchyot and Foucault: Drug Users and Migrants in Post-Soviet Central Asia and Russia

Abstract In this paper, we unpack the uchyot (“registration”) system using Foucault’s regime-based approach. Uchyot is a Soviet tool for controlling populations by requiring them to register personal information and then sharing this information with the relevant state institutions. This paper explores how uchyot is used to control drug users in Uzbekistan and Central Asian migrants in Russia. It argues that social and economic pressures, combined with strict policies, push unwanted citizens and migrants to engage in risky behaviors or into the shadows of informality and illegality.

A regime-based approach for integrating wind information in spatio-temporal solar forecasting models

Spatio-temporal solar forecasting based on statistical models seldom integrates wind information. An AutoRegressive with eXogenous input (ARX) model was tested using global horizontal irradiation records from a set of pyranometers deployed in Oahu, Hawaii, USA, where northeasterly winds are predominant. When irradiance is forecasted 10-s ahead, interesting forecast skills (up to 30.8%) can be achieved when a site has upwind neighbors available. However, when forecast skill is mapped as a function of wind direction at 850 hPa (from an ERA 5 reanalysis), negative skill values can be observed when nondominant winds occur. A wind regime-based approach is proposed, where different ARX models are built for different wind direction intervals, which substantially improves the forecasting accuracy for the underperforming wind directions. When the regime definition also takes into account wind speed, the ARX model detects spatial patterns for faster winds, with several nondominant directions achieving skill scores higher than 20%. Replacing the wind reanalysis by historical forecasts from ERA 5 reduced the overall skill by less than 0.1%.

Practical Applications of Dynamic Allocation or Diversification: A Regime-Based Approach to Multiple Assets

Practical Applications Summary In Dynamic Allocation or Diversification: A Regime-Based Approach to Multiple Assets , published in the in the 2017 special multi-asset class issue of The Journal of Portfolio Management , Peter Nystrup, Bo William Hansen, Henrik Olejasz Larsen, Henrik Madsen , and Erik Lindstrom investigate a dynamic asset-allocation strategy based on increasing exposure to risky assets during periods of low volatility and decreasing exposure to risky assets during periods of high volatility. The signal to change allocation comes from a regime-switching model based on the MSCI World Index. The strategy uses a “hidden Markov model” to detect changes from a regime of high volatility to low volatility and vice versa. The authors test their model-driven dynamic strategy over the period from 1997 through 2015. They conclude that their model-driven dynamic strategy outperforms a benchmark strategy of 60% equities and 40% fixed-income. They further conclude that the optimal implementation of their strategy is to overly it on the benchmark strategy and to apply the dynamic approach to roughly 80% of the total portfolio. Implementing the strategy on 80% of the total portfolio produces the highest Sharpe ratio.

Dynamic Allocation or Diversification: A Regime-Based Approach to Multiple Assets

This article investigates whether regime-based asset allocation can effectively respond to changes in financial regimes at the portfolio level in an effort to provide better long-term results when compared to a static 60/40 benchmark. The potential benefit from taking large positions in a few assets at a time comes at the cost of reduced diversification. The authors analyze this trade-off in a multi-asset universe with great potential for static diversification. The regime-based approach is centered around a regime-switching model with time-varying parameters that can match financial markets’ behavior and a new, more intuitive way of inferring the hidden market regimes. The empirical results show that regime-based asset allocation is profitable, even when compared to a diversified benchmark portfolio. The results are robust because they are based on available market data with no assumptions about forecasting skills.

Regime resilience and presidential politics in Indonesia

ABSTRACTThis article builds on insights from the coalitional presidentialism literature and a more ideational regime-based approach to examine the reasons behind Indonesia's ongoing democratic stagnation. It argues that this stagnation is not, as institutionalists might posit, an ultimately inevitable result of the institutional setup of multiparty presidentialism. Nor is it merely a manifestation of unchallenged oligarchic domination or the cartelization of party politics as other influential approaches to Indonesian politics have argued. Instead, this article argues that presidential politics in Indonesia is above all a reflection of a complex regime configuration in which presidents need to navigate between popular demands from the electorate, the interests of powerful veto actors who use democratic procedures only as an instrument to defend their predominantly material interests, and a constantly evolving but still inefficient set of political institutions that has largely failed to ensure accountability and transparency.

Target Date Funds: A Regime-Based Approach

Target Date Funds: <i>A Regime-Based Approach</i>

Estimating the Ungauged Natural Flow Regimes for Environmental Flow Management

Regime-based approach recently becomes an important strategy while considering aquatic ecosystems in environmental flow management. The key element for supporting this strategy is long streamflow data which is usually not available for determining natural flow regimes. This study uses a back-propagation network to estimate ungauged natural flow regimes. A set of the upper reaches of Taiwan’s 42 flow stations with non-human control streamflow and at least 20 years daily flow data is used to quantify the natural flow regimes using 31 Indicators of Hydrologic Alteration (IHA). Watershed geomorphologic characteristic factors and rainfall parameters are used to classify homogeneous flow regime areas. The results show that there are three types of flow regimes from the flow stations, and each group of indicators in the IHA has different correlations with different geomorphologic characteristic factors and rainfall parameters. The results of using an artificial neural network model to estimate IHA show that the group average percent error fell from 21 % to 8 % and the average correlation coefficient was over 0.7, indicating that the model presented in this study is able to accurately estimate the natural flow regime in ungauged stations. Instead of predicting daily streamflow, this study estimates indicator values for ease of ecological water resources management.

Practical Applications of Regime-Based versus Static Asset Allocation:Letting the Data Speak

Regime shifts present a big challenge to traditional strategic asset allocation. This article investigates whether regimebased asset allocation can effectively respond to changes in financial regimes at the portfolio level, in an effort to provide better long-term results than more static approaches can offer. The authors center their regime-based approach around a regime-switching model with time-varying parameters that can match financial markets’ tendency to change behavior abruptly and the fact that the new behavior often persists for several periods after a change. In an asset universe consisting of a global stock index and a global government bond index, they show that, even without any level of forecasting skill, holding a static portfolio may not be optimal. (Less)

Regime-Based Versus Static Asset Allocation: Letting the Data Speak

Regime shifts present a big challenge to traditional strategic asset allocation. This article investigates whether regimebased asset allocation can effectively respond to changes in financial regimes at the portfolio level, in an effort to provide better long-term results than more static approaches can offer. The authors center their regime-based approach around a regime-switching model with time-varying parameters that can match financial markets’ tendency to change behavior abruptly and the fact that the new behavior often persists for several periods after a change. In an asset universe consisting of a global stock index and a global government bond index, they show that, even without any level of forecasting skill, holding a static portfolio may not be optimal.

Links between satellite-retrieved aerosol and precipitation

Abstract. Many theories have been proposed detailing how aerosols might impact precipitation, predicting both increases and decreases depending on the prevailing meteorological conditions and aerosol type. In convective clouds, increased aerosol concentrations have been speculated to invigorate convective activity. Previous studies have shown large increases in precipitation with increasing aerosol optical depth, concluding an aerosol effect on precipitation. Our analysis reveals that these studies may have been influenced by cloud effects on the retrieved aerosol, as well as by meteorological covariations. We use a regime-based approach to separate out different cloud regimes, allowing for the study of aerosol–cloud interactions in individual cloud regimes. We account for the influence of cloud properties on the aerosol retrieval and make use of the diurnal sampling of the TRMM satellite and the TRMM merged precipitation product to investigate the precipitation development. We find that whilst there is little effect on precipitation at the time of the aerosol retrieval, in the 6 h after the aerosol retrieval, there is an increase in precipitation from cloud in high-aerosol environments, consistent with the invigoration hypothesis. Increases in lightning flash count with increased aerosol are also observed in this period. The invigoration effect appears to be dependent on the cloud-top temperature, with clouds with tops colder than 0 °C showing increases in precipitation at times after the retrieval, as well as increases in wet scavenging. Warm clouds show little change in precipitation development with increasing aerosol, suggesting ice processes are important for the invigoration of precipitation.