Economic Scenarios Research Articles

Exploring the response of ecosystem service value to land use changes under multiple scenarios coupling a mixed-cell cellular automata model and system dynamics model in Xi'an, China

Land use is a crucial factor affecting ecosystem service value (ESV), and forecasting future land use changes and ESV response can guide urban planning and sustainable development decisions. However, the traditional Cellular Automata (CA) model supposes that each cell has only one land use type at each time step, neglects the mixed structure and proportional distribution of land use units, does not take into account its quantitative continuous dynamic change, and lacks the exploration of land use quantity structure and spatial pattern optimization. This study employed a novel mixed-cell cellular automata (MCCA) approach, coupled with the system dynamics (SD) model to predict the spatiotemporal pattern of land use under the natural increase scenario (NIS), economic development scenario (EDS) and ecological protection scenario (EPS) in Xi’an, China, in 2030. The equivalent coefficient method was utilized to investigate the heterogeneity distribution and sensitivity of ESV. The results demonstrated that SD-MCCA exhibited remarkable prediction accuracy and robustness. The main changes in land use in 2000–2015 were due to urban expansion, the conversion of arable land into construction land, and the conversion between grassland and arable land. The total ESV increased from 19554.36×106 CNY in 2000 to 19618.39×106 CNY under the EPS in 2030, and the contribution of climate regulation and hydrological regulation to ESV was the highest. Spatial heterogeneity of ESV revealed a certain regularity, and the high value region was chiefly concentrated in woodland and grassland with favorable ecological conditions. Land use variations under NIS and EPS improved ESV, while the ESV had a negative response to land use transformations under the EDS. This research provides a new way to identify the relationship between future land utilization scenarios and ESV, which is of great significance for the management of land resources and formulation of ecological compensation standards.

The Quantification of Non-Action Costs as an Incentive to Address Water Pollution Problems

Diffuse pollution is one type of pollution generated by agricultural, livestock, and urban runoff that is responsible for surface and groundwater pollution. As a result, the exposed population develops different diseases that affect their short, medium, and long-term quality of life. Researchers need to be able to assess the loss of quality of life in monetary terms to include this social impact in decision-making processes. Specifically, if no measure is implemented to correct the situation, these costs can be considered as the non-action costs of the social impact of water pollution. This study assesses the importance of measuring healthcare costs as a proxy for non-action costs for the economic assessment of water pollution consequences. Thanks to this analysis, it is possible to identify the health costs produced by the current environmental situation, making it possible to obtain an economic baseline scenario prior to the implementation of any project or measure. This approach is a novelty in the literature since, to date, healthcare costs have not been related to non-action costs. Including these costs in economic feasibility studies allow us to assess in detail both the social impact of pollution and the social benefits of develop water-quality improvement projects.

An economic model to assess biosecurity management strategies for marine fish farms in Hong Kong SAR

We developed an economic model for small-scale saltwater grouper net-pen farms in Hong Kong SAR of the People's Republic of China to compare economic scenarios based on implementing different biosecurity measures on farms. Our model estimated the probability of reducing endemic infections and their spread within farms. The economic outcomes of interest, including net returns and the margin of safety ratio, were evaluated under different levels of mortality (12%, 23%, and 46%), and different numbers of initial fish stock (20 K and 100 K) on farms. Our results showed that adding a strategy for prompt removal of dead fish and early treatment of disease on farms could reduce the risk of loss, but having a comprehensive biosecurity plan on a typical marine fish farm in Hong Kong was only economically advantageous when a high percent mortality (46%) was expected on the farm, and when the farm was stocked with a high number of fish (100K). Our model may explain why small-scale saltwater net-pen farmers catering to local live markets, do not adopt comprehensive biosecurity plans. According to results from scenarios specific to Hong Kong, our model suggests these plans are expensive and only pay off when expected mortalities are quite high.

Promoting the Circular Economy on an Island: Anaerobic Co-Digestion of Local Organic Substrates as a Possible Renewable Energy Source

The local waste co-digestion is an interesting option to tackle in reduced and isolated areas like the islands. The islands have limited territory and scarce fuel production. Moreover, organic waste can create serious environmental problems in soil, water and air. Anaerobic co-digestion (AcoD) is a technology fulfilling the concept of waste-to-energy (WtE) based on local resources. The valorisation of organic waste through AcoD on an island would prevent environmental impacts, while being a source of renewable energy. In this study, cow manure (outdoor and indoor), pig slurry, bird manure, kitchen waste, sewage sludge and oily lacteous waste produced on Island Terceira (Portugal) were tested in mesophilic -35 °C- Biochemical Methane Potential (BMP) co-digestion assays. The goals were to analyse the recalcitrant and high potential produced waste and to estimate the energetic supply source on the island. The cow manure and pig slurry were used as inocula and specific methanogenic activities (SMAs) were carried out. The results showed that both substrates have a significant methanogenic activity-SMA 0.11 g-COD/(g-VSS.d) and 0.085 g-COD/(g-VSS.d), respectively. All the studied combinations were feasible in AcoD, showing TS removals in the range of 19-37%; COD removals in the range 67-78% and specific methane yields from 0.14 to 0.22 L/gCOD removed, but some differences were found. The modified Gompertz model fitted the AcoD assays (R2 0.982-0.998). The maximum biogas production rate, Rmax. was highest in the AcoD of Cow+Pig+Oily and in the Cow+Pig+Sludge with 0.017 and 0.014 L/g-VSadded.day, respectively, and the lowest in Cow+Pig+Bird with 0.010 L/g-VSadded. In our AcoD studies, the bird manure limited the performance of the process, since it was recalcitrant to anaerobic degradation. On the other hand, the oily lacteous waste showed a great potential in the anaerobic digestion. The estimated biogas production, from the best-studied condition, could cover the 11.4% of the energy supply of the inhabitants. These preliminary results would prevent the environmental impact of organic waste on the island and promote the use of local waste in a circular economy scenario.

Economic Representative Scenarios for Variable Annuity Dynamic Hedging of GMMB and GMDB

Variable annuities introduce significant risk for the insurers. To control this risk, insurers generally use dynamic hedging models. In practice, calculations for dynamic hedging models for variable annuities are computationally intensive since they require many nested stochastic scenario projections with outer and inner loops. In this article, we study the relationship between the hedging errors and the descriptive statistics of economic scenarios. Then, using the relationships between the hedging errors and the descriptive statistics of the economics scenarios, we present two novel scenario selection algorithms to determine economic representative scenarios (ERS) to run for dynamic risk hedging models. We do this for guaranteed minimum maturity benefit (GMMB) and guaranteed minimum death benefit (GMDB). We also benchmark these new algorithms against a control variate algorithm and Monte Carlo simulations. One of the two proposed novel scenario selection algorithms, the adapted Clara algorithm gives a lower mean absolute deviation of the conditional tail expectation (CTE) than the control variate method and Monte Carlo simulations for the same number of scenarios. Also, 500 representative scenarios selected by the adapted Clara algorithm generate a mean absolute deviation of the CTE95 of the hedging errors approximately equivalent to 1000 (or more in some cases) Monte Carlo simulations for 5 years GMMB and GMDB.

Changes in Land Use and Ecosystem Service Values of Dunhuang Oasis from 1990 to 2030

Maintaining the integrity and stability of oasis ecosystems is an important topic in the field of ecological research. Assessment of ecosystem services and their changes can provide important support for the sustainable development of oases. This study took the Dunhuang oasis in the hyper-arid area as the research object and used 1990, 2010, and 2020 Landsat series satellite images to complete the land use interpretation by random forest classification. Then we estimated the ecosystem services value (ESV) by using benefit transfer method, and predicted the trend of ecosystem service value changes under three scenarios using the Analytic Hierarchy Process method and the patch generation land use simulation model (AHP-PLUS model). The results showed that the vegetation areas of the Dunhuang Oasis first decreased and then increased during 1990–2020. The decrease was largely due to the expansion of built-up land and farmland, and the increase was mainly contributed by the implementation of ecological protection policies. The path of changes in the ESV of the Dunhuang Oasis during 1990–2020 was well consistent with that of vegetation areas, with a maximum of 9068.15×106 yuan (in 1990) and a minimum of 6271.46×106 yuan (in 2010). Spatial autocorrelation analysis showed that urbanization reduced ESV, and the implementation of ecological policies enhanced ESV. The ESV of the Dunhuang Oasis for the year 2030 under the ecological conservation scenario could reach 7631.07×106 yuan, which is 381.1×106 yuan higher that under the economic development scenario. The ecological conservation scenario is the optimal option to achieve sustainable development of the Dunhuang Oasis. We suggested that the government should continuously enhance the protection of forests and waterbodies, reasonably restrict production and domestic water consumption, and efficiently increase the proportion of ecological water consumption. In addition, this study improved the evaluation method of oasis ESV based on the proportion of Normalized Difference Vegetation Index (NDVI) of grasslands with different coverage, which is important for improving the environment in arid areas.

What Drives Land Use Change in the Southern U.S.? A Case Study of Alabama

Land use change reflects fundamental transformations in society. To better understand factors contributing to current land use changes in Alabama, we expand on existing land use studies by employing a generalized least-square method nested in a system of equations for the analysis. We correct for endogeneity issues in our paper by incorporating a control function technique. Using repeated land use data from 1990–2018, we focus on analyzing factors affecting land use changes among timberland, agricultural, urban, and conservation land use types. Our results reveal that land quality factors influence land allocation and land use decisions. We also indicate that population density is a driver for replacing timberland for urban development and agricultural purposes. We show that interest rates are important factors in timberland use decisions as timberland investments are sensitive to capital cost. We provide a basis for future simulations of nationwide land use changes under different economic and policy scenarios, as we offer new insights and contribute to the existing knowledge into public policies that are related to land use planning and management.

The Governance and Disclosure of IFRS 9 Economic Scenarios

Extraordinary economic conditions during the COVID-19 pandemic caused many IFRS 9 impairment models to produce unreliable results. Severe market reactions, resulting from unprecedented events, prompted swift action from the regulatory authorities to maintain the financial system’s stability. Banks managed the uncertainty and volatility in the models with expert overlays, increasing the risk of biased outcomes. This study examines new ways of enhancing the governance and transparency of the IFRS 9 economic scenarios within banks and suggests additional financial disclosures. Benchmarking is proposed as a useful tool to evaluate the IFRS 9 economic scenarios and ensure effective challenge as part of a model risk governance framework. Archimedean copulas are used to generate objective economic benchmarks. Ideas around benchmarking are illustrated for a set of South African economic variables, and the outcomes are compared to the IFRS 9 scenarios published by the six biggest South African banks in their annual financial statements during the pandemic.

Survival and sustenance strategy of primary agricultural cooperative credit societies in India: a fuzzy interpretive structural modelling approach

PurposePrimary agricultural cooperative credit societies (PACSs) in India are considered to be the backbone of the last mile delivery of rural credit for landless and marginal farmers and the poorest sections of the society. Contribution of PACS in social welfare is well documented. However, in spite of being such important form of organization at the grass root level, the authors find a typical baffling phenomenon which is fluctuating growth of PACS. Given that PACS have not been able to establish a consistent growth rate, thus hindering its trajectory to become a strong and consolidated organizational form, it is natural to investigate and identify those success factors that are critical for a newly formed PACS to survive and sustain. Hence it is necessary to undertake a strategic assessment of the function of PACS and hence identify those critical success factors (CSFs). This paper aims to address this issue.Design/methodology/approachThe authors review the existing literature and conduct interview with experts and other stakeholders with the purpose to gain a view of the strategic situation of PACS in India, especially with respect to their birth and death processes and identify a set of factors that are critical to the survival and sustenance of PACS. Based on the inputs from the experts, we modelled the interrelationships amongst these CSFs using interpretive structural modelling (ISM). Further, fuzzy Matriced’ Impacts Croise's Multiplication Appliquée a UN Classement (MICMAC) analysis is performed to cluster these CSFs into four quadrants based on their influence and dependence in the system.FindingsThe findings point out that a hierarchical interconnected structure exists amongst the CSFs that influence the survival and sustenance of the PACSs. “Quality and Motivation of Management” was found to be driving all other factors so far the survival of any PACS is considered. Also the authors have found that “Loan Recovery” is the most sensitive factor that needs to be taken care of for the sustenance of PACS. These findings are in the expected line and commensurate with the conventional wisdom yet to be documented till date.Originality/valueIt is a forward-looking analysis that tries to find out the CSFs for the survival of PACS in order to face the changing economic scenario of India which is still agrarian in nature. Both in terms of research question as well as methodology, to the best of the authors’ knowledge, this is first of its kind so far PACS are concerned being one of the most important but neglected entities in India; so far the last mile rural agricultural credit delivery is concerned, this study will help the policy makers to develop a holistic viewpoint in relation to long term sustenance of PACS.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2022-0331

Knowledge representation and reasoning using interconnected uncertain rules for describing workflows in complex systems

Knowledge representation and reasoning (KRR) in complex systems (CSs) usually require facts from multiple experts having complementary backgrounds to fuse together. Consequently, such KRR methods should provide universal modeling languages close to human reasoning, with increased expressiveness and efficient capabilities to describe uncertainties. In this context, this paper introduces a new modeling formalism entitled Hybrid Logic-Algebraic Relational Modeling which is based on combining logic, probabilities, numerical information and network representations. The behavior, facts and workflows in a CS can be described using an environment of interconnected models enclosing sets of logical rules with attached probabilistic trust factors and links regarding logical attributes and numerical parameters. The logical and probabilistic inference applied to the modeling environment gives valuable knowledge to designers and decision-makers so that they can develop procedures or take actions in managing the CS. In this article, the proposed approach is completely formalized, from concept to definition and proofs and up to implementation, while its usage is illustrated within a complex economic, logistical, economical and technical scenario.

Sustainability as an Aid to the Interpretation of the Economic Scenario

Is it possible that the principles of sustainability economy offer some more inspiration in our eternal attempt to look beyond the present time? This hypothesis certainly cannot be denied, because we must choose between a kind of development positive for nature and another kind forged instead by the human selfishness. Some help to stay in the right direction are the useful aid offered by nature (universal and constant laws in economics) and the curative character of natural interventions implemented when we derail from the correct path of constant growth. As saying that the irregularities of false development, starting with the conjuncture cycle and its companions (inflation and deflation), are a real protection from the danger of an irreparable fall of the economic mechanism and then of whole civilization. The fact remains certain that once off the path of constant development, the correction introduced precisely by the conjuncture cycle is certainly painful and somewhat complicated. Nevertheless, it offers some opportunities to find the way out of the imbalance. Thus, believing that long-term deflation can be overcome with ultra-Keynesian remedies means to suppose that we can control the economic cycle and its evolutions. But unfortunately, it does not work that way. And are equally unfounded the suppositions that see in speculation - which takes the financial market away from real values – a way to help the weak and depressed economy within a deflation scenario. Still on this subject, the choice of Central Banks to follow or anticipate - in the event of deflation - the drop-in interest rates down to zero or even below, should be limited by introducing a lower threshold that should not be exceeded when interest rates are falling. Because otherwise the excited speculation, so fueled, will lead us to a probable financial crisis. Instead, it is just an irregularity created by the abandonment of constant growth with minimal damage to nature. An irregularity on the development path that we have identified as the sub-world. On the other hand, we should not forget that the community or rather its majority is the only accredited counterpart of the forces of nature, so the close alliance between a good governance and the community is the key to maintaining or rediscovering the path of constant growth with minimal damage to nature.

Sustaining Business Performance Management: An Operational Framework

This article explores an increasingly important theme for all business sectors: sustainability and its linkage to business performance management, and proposes an operational framework based on the Balanced Scorecard model. Enterprise sustainability is a subject that is extensively being assessed and measured in various industries nowadays. We focus on Chilean SMEs and explore how a sustainability trend led by technology-related innovation and performance measurement systems can enable and allow to maintain sustainable enterprises through the today's volatile, uncertain and complex socio political and economic scenario. Worldwide, issues such as sustainability, innovation and social responsibility are driving business performance management (BPM) of thriving companies, many of which champion for greater social equity, business sustainability and fairness. This process entails a paradigm shift that is particularly noticeable in small and medium size enterprises or SMEs―the largest segment of Latin America's businesses, and especially so in Chile, a country which, according to OECD 2022’s Table 8.2. Distribution of firms in Chile, 2018, SMEs account for over 90% of the enterprises in the country.

Produção e avaliação econômica das raças ovinas Corriedale, Highlander e Milchschaf no Sul do Uruguai

ABSTRACT: Sheep production is expanding among small farmers in Southern Uruguay. Currently, Corriedale and Milchschaf are being used, but not Highlander. However, there is lack of experimental information regarding the relative performance of these breeds. We conducted an experiment where these three sheep breeds were run together at the Southern Regional Centre, located in the region in question. Wool, body, reproductive and lamb growth traits were recorded from 2015 to 2019. Results were used as a basis for the calculation of gross margins for each breed, which we calculated for a range of production and economic scenarios. For scenarios based on the results of the present study Highlander was the best performing breed. If it was assumed to be wool-less, it performed even better. In some scenarios Corriedale performed best, especially when the higher wool price it used to enjoy was assumed. However, fetching such a price in the foreseeable future is unlikely. We concluded that in the absence of wool-less sheep that perform in a manner similar to Highlander or Milchschaf in terms of reproduction and lamb growth, Highlander is currently the best option for small farmers in Southern Uruguay. Until now, Milchschaf has been the recommended breed for the region and production system in question. The recommendation should be reviewed, Highlander should be recommended instead, and the performance of wool-less breeds should be investigated. Results could be applicable to other temperate regions in Latin America where similar production systems exist or may be developed.

Flash Flood Risk Assessment in the Context of Economic Change Scenarios

Abstract Flash flood disasters pose a constant threat to socioeconomic factors in southeastern China. This study analyzes the risk change of flash floods in the Yantanxi River basin, southeastern China, under five economic scenarios [shared socioeconomic pathways (SSPs); SSP1, SSP2, SSP3, SSP4, and SSP5]. We built a regional flash flood hazard assessment model by combining hydrological and hydrodynamic models with fieldwork. Asset value was used to represent regional exposure, which was spatialized using data from industrial structure and land use. Flash flood risk assessment influenced by economic change was developed using different industry responses to flash floods. The results clarify how economic factors drive flash flood risk changes. The return period of the 2019 flash flood in the Yantanxi River basin is 150 years. In 2019, flash floods affected 5.04% of the river basin; the inundation depth was concentrated at under 2.00 m, resulting in CNY 0.55 billion in economic damage. With economic change, the flash flood risk increases by 91.34% (SSP2—current economic development level) and 94.39% (SSP5—extreme economic development level). This study emphasizes the balance between economic development and disaster management at the river basin scale; in addition, our method provides a reference for risk assessment in flash-flood-prone areas lacking statistical information. Significance Statement The mountainous and hilly areas of southeastern China are vulnerable to flash floods, and the region faces a constant threat from flash flood disasters. The analysis of historical flash flood disaster events is a critical step in understanding the current rank of the disaster risk and its changes over time. The Supertyphoon Lekima–extreme precipitation–flash flood chain effects resulted in severe economic damage and casualties within the Yantanxi River basin, Zhejiang Province, in August 2019, thus raising concerns about the characteristics of flash floods within the region. The study results highlight the importance of flood risk management in regional adaptation strategies and provide new information for regional planning and the construction of flood control facilities.

Correlation regression based forecast of Gazprom PJSC stock quotes

Introduction. A scientific research examining the concern of Gazprom PJSC (a leading Russian energy company) stock quote forecasts is relevant because it could determine investment prospects in the stock market of the Russian Federation. The key idea of this work is to find the most profitable and investable Russian company and outline the factors among many others that affect its stock quotes. Purpose . The author attempts to construct multiple linear regression equations reflecting the impact of the economic factors (the prices of the American natural gas, the USD/RUB currency pair, the M2 monetary aggregate in Russia) on the Gazprom PJSC stock quotes. These multiple linear regression equations are used to develop economic and mathematical models with the projected values of the factors. Materials and Methods . The paper refers to the general and special scientific methods – analysis, synthesis, a monographic method, and statistical methods – graphs, tables, trend spotting, correlation and regression analysis. The choice of independent variables in the correlation and regression analysis was driven by several factors: global natural gas prices determine the fi nancial performance of the Russian energy companies; the revenue of the Russian exporters has long been dependent on the USD/RUB currency pair; security quotes rose at the stock markets due to the monetary policy of central banks which strive to build up the monetary supply. Results. The study developed the equations of multiple linear regressions for the selected four periods with different economic scenarios. This proves the relevancy of the issue under analysis. These equations reflect the dependence of the Gazprom PJSC stock quotes from the prices of the American natural gas, the USD/RUB currency pair, and the money supply in Russia. They could give rise to the economic and mathematical models with the projected values of the analyzed factors and their possible correlations. Conclusion . The economic factors in question could have a positive impact on the Gazprom PJSC stock quotes against a weak Russian ruble and the national energy companies refocusing their attention on other markets. This information could be of use for the economic entities to boost their investment performance.

Post-COVID-19 economic growth scenarios for Mexico City

Post-COVID-19 economic growth scenarios for Mexico City

IMMEDIATE EFFECTS OF COVID-19 PANDEMIC SITUATION ON LIVELIHOOD OF WOMEN CULTIVATORS IN THE COASTAL AREAS OF WEST BENGAL AND ODISHA

India is known for its dependence on agriculture and allied sectors as the major pillar of its economy. Being one of the major emerging nation in the world’s economic and political power scenario the country has been expected to stand in good position in terms reduction of poverty and livelihood development of the people particularly of the rural area. The spread of Covid-19 virus has attributed to huge economic squander worldwide and India is no more any exception, rather the economy is such badly affected due to this situation that the GDP growth has brought down to only 23.9% over the same quarter last fiscal. Due to the current pandemic situation a large portion of global population is in a deadly juncture for its livelihood options due to sudden unemployment and related poverty along with. High risk of getting infected by this deadly virus and it’s after effects. Specifically, the poor rural community who are largely dependent on agriculture and labour work are the worst hit ones due to this present situation. In this perplexing time being the vulnerable section women are again the most affected ones. This paper aims to understand the current situation and its immediate effect on the women cultivators of coastal parts of West Bengal and Odisha; the study also aims to find major facts towards their attitude of alternation of livelihood strategies. The study has been done exclusively on primary data.

Anti-Competitive Agreements

In a constantly evolving economic scenario, the need for enactment of competition laws became apparent, The Competition Act of 2002 has been implemented to promote competition and ensure freedom of business. One of the major objectives of the competition act is to ensure that the concentration of economic power does not reside in the hands of a few affluent business houses. In a bid to fulfill this objective, the Competition Act of 2002 prohibits parties from entering into anti-competitive agreements. This is done to ensure smooth market functioning and protect the interests of the consumer. Therefore, parties to an agreement, although possess the freedom of trade, they cannot enter into an agreement that might be anti-competitive in nature.

Econometric model of iron ore through principal component analysis and multiple linear regression.

Price of iron ore is affected by instabilities of microeconomic balance between supply and demand. Periods of equilibrium adjustment result in huge swings, growth or global recession. They also impact the viability of mineral enterprises and generate consequences to important global economic scenarios. This research aims to evaluate the market variables capable of influencing the price of iron ore through multivariate statistical techniques. Principal component analysis and multiple linear regression, booth multivariate statistical techniques were used. The studied variables were rate export of iron ore and concentrates from Brazil, steel production from China, steel production from Japan, production from Europe, steel production from the United States, steel production from India, steel price, coal price, China's Construction Gross Domestic Production, United States construction index, oil price and global oil production. First three components explained 89.12% of the variability of the data matrix. Multiple linear regression highlighted the significance of five variables. They are export iron ore from Brazil, steel production from China, price of coal, steel production from India and price of steel.

Effect of SSRI on C-Reactive Protein in Case of Depression

Introduction: Depression can present with several symptoms, such as loss of pleasure, feelings of guilt, low selfesteem, and disturbed sleep or appetite. In recent socio- economic scenario incidence & prevalence of depressionis on increasing trend. SSRIs are the mainstay of treatment of depression.Objective: the anti-inflammatory role of escitalopram in freshly diagnosed depression case and also to find anycorrelation between depression & inflammation.Material & Methods: It was a cross-sectional analytical study conducted at College of Medicine and Sagore DuttaHospital by Department of Biochemistry in collaboration with Department of Psychiatry. 71 Patients attendingpsychiatric OPD who are newly diagnosed as Major depressive disorder (MDD) were selected. 73 Age and sexmatched healthy family members of the patients were taken as controls.Before starting treatment C reactive protein(CPR) & Hamilton depression rating scale (HAMD) was assessed. After 12 weeks of treatment same parameterswere assessed again.Results: after 12 weeks of treatment mean CPR & HAMD score is significantly reduced in case group as comparedto the baseline values respectively. The reduction of HAMD score is negatively correlated with the baseline CPR.Conclusion: Escitalopram significantly reduce the CPR value which may have a role in improvement of HAMDscore.