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This paper aims to estimate a New Keynesian small open economy dynamic stochastic general equilibrium (DSGE) model for Egypt using Bayesian techniques and data for the period FY2004/2005:Q1-FY2015/2016:Q4 to assess monetary and fiscal policy interactions and their impact on economic stabilization. Outcomes of monetary and fiscal authority commitment to policy instruments, interest rate, government spending and taxes, are evaluated using Taylor-type and optimal simple rules.

The study extends the stylized micro-founded small open economy New Keynesian DSGE model, proposed by Lubik and Schorfheide (2007), by explicitly introducing fiscal policy behavior into the model (Fragetta and Kirsanova, 2010 and Çebi, 2011). The model is calibrated using quarterly data for Egypt on key macroeconomic variables during FY2004/2005:Q1-FY2015/2016:Q4; and Bayesian methods are used in estimation.

The results show that monetary and fiscal policy instruments in Egypt contribute to economic stability through their effects on inflation, output and debt stock. The monetary policy Taylor rule estimates reveal that the Central Bank of Egypt (CBE) attaches significant importance to anti-inflationary policy and (to a lesser extent) to output targeting but responds weakly to nominal exchange rate variations. CBE decisions are significantly influenced by interest rate smoothing. Egyptian fiscal policy has an important role in output and government debt stabilization. Additionally, the fiscal authority chooses pro-cyclical government spending and counter-cyclical tax policies for output stabilization. Again, past values of the fiscal instruments are influential in the evolution of the future fiscal policy-making process.

A few studies have examined the interaction between monetary and fiscal policy in Egypt within a unified framework. The presented paper integrates the monetary and fiscal policy analysis within a unified dynamic general equilibrium open economy rational expectations framework. Without such a framework, it would not be easy to jointly analyze monetary and fiscal transmission mechanisms for output, inflation and debt. Also, it would be neither possible to contrast the outcome of monetary and fiscal authorities commitment to a simple Taylor instrument rule vis-à-vis optimal policy outcomes nor to assess the behavior of monetary and fiscal agents in macroeconomic stability in context of an active/passive policy decisions framework.

This paper aims to understand the significant farm and market-level factors that incentivize the adoption and marketing of pulses influencing its supply response to changing demand.

The authors first use a modified Nerlovian supply response model using secondary data to identify the major price and non-price factors influencing the supply of pigeon pea, black and green gram in the major pulses growing states in India. Second, using primary qualitative data the authors map the pulses value chain from farm to retail to identify the how proportional and fixed transaction costs (FCTs) influence market participation of pulses growers and limit the transmission of price and quality information.

The supply response model shows some positive influence of price on area allocation for pigeon pea and black gram and some negative effects of yield and price increase of competing crops on pigeon pea acreage. However, for the most part, the area of Kharif pulses is inelastic to prices in the long run. Irrigation, rainfall and yields in the lag year are shown to have a significant influence on area allocation for pulses. The market study reveals that low yields, low landholding size and geographical disadvantages of high agro-climatic risk and poor connectivity hinder market access of pulses farmers relative to other crops. Market power in favor of buyers and poor price and quality information is a disadvantage to sellers, influencing their ability to participate in markets.

A quantitative study would be required to identify the magnitude of farm and market-level transaction costs.

This study helps to understand the supply response of pulses and gives suggestions to direct policy to rectify this.

The purpose of this paper is to analyze the credit channel effects on investment behavior for the US and the Euro area.

This paper uses the dynamic stochastic general equilibrium model and calibrates a version of the Carlstrom and Fuerst’s (1997) agency cost model of business cycles with time-varying uncertainty in the technology shocks that affect capital production. To highlight the differences between the US and European financial sectors, the paper focuses on two key components of the lending channel: the risk premium associated with bank loans and the bankruptcy rates.

This paper shows that the effects of minor differences in the credit market translate into large, persistent and asymmetric fluctuations in real and financial variables and depend on the type of shocks. The results imply that the Euro areas supply elasticities for capital are less elastic than that of the USA following a technology shock. Finally, the authors find that the adverse impact of uncertainty shocks is heterogeneous across countries and amplified by the steady-state bankruptcy rate and risk premium.

This paper quantifies the effects of uncertainty shocks when there is a credit channel due to asymmetric information between lenders and borrowers for the Euro area countries, and then compares the results to that of the USA. This paper shows that financial accelerator mechanism could potentially play a significant role in business cycles in the Euro area. This result directly lends one to conclude the following: the credit channel that affects the financial sector does indeed matter for macroeconomic behavior, and that policy makers should be attentive in smoothing out uncertainties if the economic policies are to lower the business and financial cycle volatilities.

The objective of this research is to propose a framework which is apt to assess how a nation branding campaign could promote cultural identity by ultimately curbing political polarization.

By relying on a multidisciplinary approach that blends theoretical constructs from different fields the methodology is based on a mixed-method approach whereby the qualitative data stemming from a set of interviews with key-informants is coupled by a survey of Colombian citizens in order to gain in-depth insights over the impact of nation branding on political polarization.

From the findings, it emerges that a campaign based on nation branding and targeting domestic citizens could curb political polarization within Colombia, by also fostering cultural identity.

The study considers only Colombia. To fully assess the robustness of the framework it would be useful to extend the analysis to a broader range of countries and to a wider set of domestic issues.

The research not only provides in-depth insights on how nation branding can be used effectively in order to curb political polarization but also practical guidance on how a nation branding campaign can be effectively designed. The findings are relevant to policy-makers that have the opportunity to implement informed and educated nation branding campaigns not just overseas, but also to strategically address important domestic issues by engaging the domestic stakeholders.

While country branding has been extensively investigated within the context of international business, we have a relatively limited understanding of its domestic impact. In contrast to traditional country branding literature, this paper aims to theoretically advance our understanding of nation branding and its effect on political polarization, as well as gauging its impact on cultural identity.

The authors explore the hypothesis that some movements in commodity prices are anticipated (news shocks) and can trigger aggregate fluctuations in small open emerging economies. This paper aims to discuss the aforementioned objective.

The authors build a multi-sector dynamic stochastic general equilibrium model with endogenous commodity production. There are five exogenous processes: a country-specific interest rate shock that responds to commodity price fluctuations, a productivity (TFP) shock for each sector and a commodity price shock. Both TFP and commodity price shocks are composed of unanticipated and anticipated components.

The authors show that news shocks to commodity prices lead to higher output, investment and consumption, and a countercyclical movement in the trade-balance-to-output ratio. The authors also show that commodity price news shocks explain about 24% of output aggregate fluctuations in the small open economy.

Given the importance of both anticipated and unanticipated commodity price shocks, policymakers should pay attention to developments in commodity markets when designing policies to attenuate the business cycles. Future research should investigate the design of optimal fiscal and monetary policies in SOE subject to news shocks in commodity prices.

This paper contributes to the knowledge of the sources of fluctuations in emerging economies highlighting the importance of a new source: news shocks in commodity prices.

The purpose of this paper is to evaluate the interest rate (IR) sensitivity of output and prices in developing economies with different levels of financial inclusion (FI) for the period 2007Q1–2017Q4.

By using the PCA method to construct an FI index for each country, the author divides the sample into two groups (high and low FI levels). Then, with panel vector autoregressions on per group estimated to assess the strength of the impulse response of output and prices to IR shock.

The findings show that the impact of an IR shock on output and inflation is greater in economies with a higher degree of FI.

The finding indicates the link between FI and the effectiveness of IRs as a monetary policy tool, thereby helping Central banks to have a clearer goal of FI to implement their monetary policy.

This study emphasizes the important role of FI in the economy. From there, an FI solution is integrated into the construction and calculation of its impact on monetary policy, improving the efficiency of monetary policy transmission, contributing to price stability and sustainable growth.

The purpose of this paper is to explore and analyse the dynamic relationship between remittances inflows of Egyptians working abroad and asymmetric oil price shocks.

This study uses a vector autoregressive (VAR) model to explain the impulse response functions (IRFs) and the forecast error variance decomposition (FEVD). The rationale behind using these tools is its ability to examine the dynamic effects of our variables of interest.

The impulse response functions confirmed that remittance inflows have various responses to asymmetric oil price shocks. For instance, inflowing remittances increase in response to positive oil price shocks, while it decreases in response to negative oil price shocks. Also, the results indicate that the responses are significant in the short and medium-run and insignificant in the long run. The magnitude of these responses reaches its peak or trough in the third year. Further, the variance decomposition reveals that oil price decreases are more influential than oil price increases.

This means that remittances inflows in Egypt are pro-cyclical with oil price shocks. That explained by the fact that more than one-half of those remittances sent from GCC countries where real economic growth is very pro-cyclical with the oil prices. This empirical assessment will help policymakers to determine the behaviour of remittances and highlights the impact of different kinds of oil prices shocks on remittances. Unlike the little existing literature, this study is the first study applied the VAR model using a novel dataset spanning 1960-2016.

The authors estimate the multiplier effect of government public infrastructure investment in Spain. This paper aims to use annual data of the 17 Spanish autonomous communities for the 1980–2016 period.

The authors use dynamic acyclic graphs and the heterogeneous panel structural vector autoregressive (P-SVAR) method of Pedroni (2013). This method is robust to cross-sectional heterogeneity and dependence, which are present in the data.

The findings suggest that an increase in the level of government public infrastructure investment generates a positive and persistent effect on the level of output. Five years after the fiscal expansion, the multiplier effects of government public infrastructure investment reach values above one. This confirms that government public infrastructure investment expansions have Keynesian effects. The authors also find that the multiplier effects differ between autonomous communities with above-average and below-average GDP per capita.

To the best of the authors’ knowledge, no research uses dynamic acyclic graphs and heterogeneous P-SVAR techniques to estimate fiscal multipliers of government public investment in Spain by using subnational data.

Sustainable manufacturing is one of the most important and most challenging issues in present industrial scenario. With the intention of diminish negative effects associated with cutting fluids, the machining industries are continuously developing technologies and systems for cooling/lubricating of the cutting zone while maintaining machining efficiency. In the present study, three regression based machine learning techniques, namely, polynomial regression (PR), support vector regression (SVR) and Gaussian process regression (GPR) were developed to predict machining force, cutting power and cutting pressure in the turning of AISI 1045. In the development of predictive models, machining parameters of cutting speed, depth of cut and feed rate were considered as control factors. Since cooling/lubricating techniques significantly affects the machining performance, prediction model development of quality characteristics was performed under minimum quantity lubrication (MQL) and high-pressure coolant (HPC) cutting conditions. The prediction accuracy of developed models was evaluated by statistical error analyzing methods. Results of regressions based machine learning techniques were also compared with probably one of the most frequently used machine learning method, namely artificial neural networks (ANN). Finally, a metaheuristic approach based on a neural network algorithm was utilized to perform an efficient multi-objective optimization of process parameters for both cutting environment.

The purpose of this paper is to summarize different methods of constructing the financial conditions index (FCI) and analyze current studies on constructing FCI for China. Due to shifts of China’s financial mechanisms in the post-crisis era, conventional ways of FCI construction have their limitations.

The paper suggests improvements in two aspects, i.e. using time-varying weights and introducing non-financial variables. In the empirical study, the author first develops an FCI with fixed weights for comparison, constructs a post-crisis FCI based on time-varying parameter vector autoregressive model and finally examines the FCI with time-varying weights concerning its explanatory and predictive power for inflation.

Results suggest that the FCI with time-varying weights performs better than one with fixed weights and the former better reflects China’s financial conditions. Furthermore, introduction of credit availability improves the FCI.

FCI constructed in this paper goes ahead of inflation by about 11 months, and it has strong explanatory and predictive power for inflation. Constructing an appropriate FCI is important for improving the effectiveness and predictive power of the post-crisis monetary policy and foe achieving both economic and financial stability.