Impact of Natural Disasters on the Economy of Pakistan

Impact of Natural Disasters on the Economy of PakistanNatural disasters atomic chip 18 an progressively phenomena that we all evidently observe and identify that whitethorn have a direct bang on the interests of an atomic number 18a where it hits and also on explicit interior(prenominal) meters in much(prenominal) beas. Depending of where we zippy, hurri toilettees, earthquakes, floods, droughts, etc, argon intimidation to living, belongings, industrious assets, and also can have an bushel on societal pointers.The increasing incident of indispensable disasters is extremely inter associate to the increasing susceptibility of homes and communities in emergent nations, as earlier socio scotch vulnerabilities may aggravate the shock of a lifelike disaster, making harder the line of revitalization (Vatsa and Krimgold, 2000). Therefore, the extend to of such until nowts could consequence in an instant raise in p everywherety and deficiency (Carter et al, 2007). The liter ature has been still conflicting to a fewerer amounts. For showcase Benson and Clay (2003) have discussed that the long-standing shock on information of natural disasters is depressing, at the same time as Skidmore and Toya (2002) explain that such tragedy may upbeat preserve development in the long run as in that location is a decrement to returns on physiological assets but a push in human capital, leading to advanced development. Strobl (2008) for the US coastal areas discover that tornados reduce countys development originally by 0.8 per cent, whereas getting your strength back by and byward in 0.2 per cent. This writer also figures come to the fore for Central America and the Caribbean that the impact from a critical cyclone is a diminution of 0.8 percent of development (Strobl, 2008a).The impact of a natural disaster may also origin discriminations. The poor, who undergo from profits rise and fall, and also have imperfect access to monetary services, in the consequ ences of a disaster may be extra flat to lessen use and have a declining overrule in another(prenominal) domestic indicators as a result. Additionally, thither are a m some(prenominal) non poor, or close to be, who are not insured in opposition to such threats, and then may plunk down into scarcity as result of recapitalizing when dealing with with the upset, depending the shock and probability of diminishing into scarcity of the original stock assets and coping means.Furthermore, susceptibility to natural disasters is a multifaceted issue, as it is strong-minded by the financial structure, the phase of product, prevailing of communal and fiscal conditions, coping means, risk evaluation, rate of recurrence and concentration of catastrophes, etc. The impact on deprived ones could be losing contact with a few vital services, reversals in accretion of corporeal and human funds, and possibly an augment in barbarian oeuvre and unlawful behavior.Lindell and Prater (2003) summate t he significance of shaping the impact and the pretentious agents in natural disasters. First, that information is helpful for policy makers, as they can be acquainted with the need for peripheral support and which may be more efficient scrap, definite sections of affected can be acknowledged, e.g. how low income families are affected and third, it may be also practical for setting up assistance for natural disasters and the latent results.Overall, growing literature has emerged over the last few years on the macroeconomic and development impacts of natural disasters. Amusingly, there is as up till now no harmony on whether disasters are epochal from a macroeconomic point of view, and two situations can be identified. The first believes natural disasters a hinder for economic development and is well symbolized by the followers referenceIt has been argued that although individuals are risk-averse, governments should take a risk-neutral stance. The reality of developing countries su ggests otherwise. Government decisions should be based on the opportunity costs to society of the resources invested in the go steady and on the red of economic assets, functions and products. In view of the responsibility vested in the public sector for the administration of scarce resources, and considering issues such as fiscal debt, passel balances, income distribution, and a wide range of other economic and social, and political concerns, governments should not act risk neutral (OAS, 1991).The other position sees disasters as entailing little growth implications and consider disasters and their reduction a problem of, but not for development (e.g. Albala-Bertrand, 1993, 2006 Caselli and Malhotra, 2004). These authors find natural disasters do not minusly affect gross domestic product and if anything, GDP growth is improved (Albala-Bertrand, 1993 207). This paper can be understood as an attempt at reconciling this body of literature. There are two gate points for the analy sis. The first is to look at counterfactual vs. observed GDP, the second entry point is to assess disaster impacts as a function of hazard, exposure of assets (human, produced, intangible), and, fundamentally vulnerability.Overall, the evidence reveals adverse macroeconomic consequences of disasters on GDP. In a medium- landmark analysis, natural disasters on average seem to lead to negative make on GDP. The negative effects may be small, yet they can become more pronounced depending on the size of the shock. We tested a large number of vulnerability predictors and found that higher support rates as well as higher remittances lessen the adverse macroeconomic consequences, while capital stock impairment is the well-nigh important predictor for the negative consequences.In July-August 2010, Pakistan experienced the worst floods in its history The floods have affected 84 districts out of a measure 121 districts in Pakistan, and more than 20 million people one-tenth of Pakistan s population More than 1,700 men, women and children have lost their pass aways, and at least 1.8 million homes have been discredited or destroyed (UN 2010, p.1). In attacking poverty in developing countries, due considerations need to be paid to the vulnerability of households against natural disasters. Poor households are likely to suffer not only from low income and consumption on average but also from fluctuations of their welfare once such disasters occur. These households are dangerous to a decline in their welfare take because they have limited ability to cope with shocks and also they are subject to substantial shocks, such as weather variability (Dercon, 2005 Fafchamps, 2003).This concern has led to an emerging literature on vulnerability measures in development economics (Ligon and Schechter, 2003 2004 Kamanou and Morduch, 2005 Calvo and Dercon, 2005 Kurosaki 2006a). We broadly think people as vulnerable when (i) they cannot mitigate income volatility and (ii) their con sumption expenditure is volatile over time (they lack reliable coping mechanisms). Vulnerability is thus a advanced(a) concept.As an example of low-income countries subject to substantial vulnerability, this paper examines the bailiwick of Pakistan. Pakistan is located in South Asia, where more than 500million people or about 40% were mindd to live below the poverty line at the turn of the century (World Bank, 2001). Economic development in South Asia has been characterized by a moderate success in economic growth with a substantial failure in human development such as basic health, education and gender equalizeity (Dreze and Sen, 1995). This symptomatic is most apparent in Pakistan (World Bank, 2002). Although the overall economic growth rates were improved during the 2000s, poverty reduction was slower than expected. using a two pointedness panel dataset spanning three years from the North-West Frontier Province (NWFP), one of the four provinces comprising Pakistan, Kurosak i (2006a) and Kurosaki (2006b) show that rural households were indeed vulnerable to substantial welfare fluctuations. Using a three-year panel dataset from Pakistans Punjab, Kurosaki (1998) shows that farmers consumption was excessively sensitive to idiosyncratic shocks to their non-farm income. Similar findings have been accumulated for rural India as well (Townsend, 1994 Kurosaki 2001).The paper is organized as follows. Section 2 reviews the literature on the macroeconomic impacts of disasters and locates the proposed analysis within the disaster risk management paradigm. In section 3, we present the data and methodological analysis used for projecting the economic impacts for a medium term horizon (up to 5 years after an event), as well as the regression analysis used for identifying predictor variables explaining potential impacts. Section 4 ends with a discussion of possible implications of our analysis.Literature ReviewThe literature on impacts of natural disasters and econom ic effects is still inad liken and can be separated generally into three different categories. One take off of the literature has focused on how several factors come out susceptibility to natural events. They have maintained a natural vulnerability framework in view of climate change, deforestation and geophysical factors (McGuire, Mason and Kilburn, 2002), other than rising urbanization which brings ecological risks and exposure to threats from deficiency of sufficient urban development and dual political discourse (Pelling, 2003 and 2003a), or even environmental immediate apprehension to exposure, access to property and public conveniences as well as political and social networks (Bosher, 2007).All these parts become a thread to population, their assets and possessions and their high-power competence, becoming then an expected risk. And when such danger is realized, then it turns out to be a natural adversity (see McGuire, Mason and Kilburn, 2002). Although this thread of the literature distinguishes that such risk factors fascinate the impact of the natural tragedy, they just briefly point out essentially the number of losses, or some irregular overheads.A second thread of the literature spotlights on the impact of natural disasters on macroeconomic pointers. Auffret (2003) examined the impact of natural catastrophe on Latin America and the Caribbean, and figured out the impact very considerable, particularly for the Caribbean, where the explosive nature of expenditure is higher than in other parts of the world, where insufficient risk-management instruments have been operable in the region.This part of the literature has been still conflicting to some extent. For example Benson and Clay (2003) have also explained that the lasting impact of natural events on economic development of any country is negative, while Skidmore and Toya (2002) reveal that such tragedies may also have a constructive impact in the future growth, resulting from a decrease to re turns to physical assets but an enlargement in human capital.Strobl (2008) discovers for the US coastal counties that cyclones cut districts intensification at first by 0.8 per cent, at the same time as recuperating after in 0.2 per cent. This writer also figures out for Central America and the Caribbean that the impact from a unhelpful storm is a decline of 0.8 percent of fiscal amplify (Strobl, 2008a).When investigating what extra features cut or amplify the impact of such natural tragedies on macro pointers, Kahn (2005) and Toya and Skidmore (2007) explain that organizations, top education and trade openness, in summation to well-built economic segment and smaller governments are significant aspects in shaping the impact that natural events have on growth at planetary level.The third tributary of the literature takes care of the impact and coping means for such tragic events generally at the domestic and township levels. At this point, natural adversities are upsets that famil y units have to face as they are unpleasant proceedings leading to a decline in earnings or utilization, and in addition a loss in industrious property.Alderman et al (2006) by means of data for family units in Zimbabwe spotlighted on height growth of kids as result of a deficiency and civil war in Zimbabwe, result that kids influenced by such upsets have less naturalizeing and could have been tall if not. Dercon (2004) focused on development in utilization amongst family units in chosen villages in Ethiopia, and did not discover that upsets have an effect in the diminution of assets.Carter et al (2007) examined the impact of droughts in Ethiopia and of cyclone Mitch in Honduras on development of belongings at the village level. For Ethiopia they uncover a feigning of assets leveling between low income family units, i.e. such families keep hold of their assets even they are little in phases where profits and usage drops off, for instance the big deficiency aroused. They discover f or Honduran families that comparatively well-off families recovered earlier from the upset than short income households, and that a poverty corner is put below a specified point of income. Baez and Santos (2007) also examined the sound effects of Mitch on households pointers, discovering no moment on school admissions of kids, but a noteworthy add to their labor contribution.Others have investigated how some coping methods inside families have an effect on revivification from a shock resulting from such an adversity. De Janvry et al (2006) explains that uncertain cash transfer accessibility before a disaster provide as a comfort for those who are affected, while those dependent and helpless people utilize as coping method an add to child labor, and savings in food and school expenses. Alpizar (2007) also discovers that access to proper economic services takes the edge off pessimistic outcomes from natural disaster upsets for farmers in El Salvador, as it leads to further accompl ished production.On the other hand, a less urbanized region is the impact at local level. Yamano et al (2007) explain about industries and production. These writers makes use of region-wise data for employment and production, guessing that financial fatalities are not in proportion to the sharing of manufacturing activities and people attention, signifying that strategies to improve losses should be measured from a top order. Burrus et al (2002) also examined how low intensity typhoons can shock local financial systems from side to side interruption of actions. They exercise statistics from the local Chambers of Commerce surveys and as a result of their regularity the bang could be a decrease between 0.8 and 1.23 per cent of yearly production and up to 1.6 per cent of local employment.Though, there is a slit in the study of how local communal indicators are exaggerated by natural events. This is significant to bring to the front as the effects give the impression of being stretch ar ound all unlike points, macro, micro and local, and how strategies to deal with those upsets can be premeditated in a legal way.Whereas families emerge as the natural component of investigation for researching the consequences of natural disasters, it can also seem right to balance the study up as families oppose to risks are frequently influenced by the broader strategy framework. Certainly, households have substantial and insubstantial assets at their clearance, and their capability to preserve or gather together such assets in such situations will be produced by the arrangements and procedures for instance governance and institutional planning, broader strategies and open serving at metropolitan and district level.Additionally, the experience of family units to danger loss can and has been conventionally balanced up to top levels of aggregation (UNDP, 2008). It is the number of citizens situated in definite parts joint with the individual, material and ecological conditions o f families and the regions where they live that forms their communal potential to deal with a natural disaster. For that reason, we refer to the community level of study while thinking of the inferences that dangers can have.Governments have a disposal to go on board in various approaches to deal with natural happenings. In the past, they have usually reacted through disaster fireman, but more belatedly there has been a propensity to highlight cash transfers as well. Even if both methods are select extra efficiency could be consummate by adopting danger diminution and improvement means that deal with the structural aspects which make families more uncovered to natural risks. Having system in position previous to the sentiency of dangers is primary.At the macro level, premature warning systems and the public disaster-preparedness agenda look as if mostly significant, so as sufficient economic assets to promote revival, over and above tax inducements for households or public to t ake on mitigation procedures.Another event of protecting the value of material goods at the macro level could be through financial diversification. Increasing primary, secondary and tertiary sector activities along with spatial activities in the economy, can offer an open pool to cover the risk of anguish danger losses, and extra prospects to amplify and steady profits. Equally, the concentration of financial and sector-wise activities would be reliable with condensed capability of families to administer and react to natural disasters.Still, there is a set of insubstantial facts which might improve the family hard work to get through the outcome of natural vulnerability on them, just as adverse socio-economic opportunities. The political economy and organizational aspects of the situation where assets are positioned together with the system of belief, norm and ideas set in the activities of communities members might bear out dim-witted while utilizing and mobilizing assets for co nfronting disasters. If possible, one should be capable to clarify how civilization and supremacy provision come into play when they act together with the broader surroundings of risks, assets and wellbeing results. However, most of these features will be tough to get into work empirically for the period of our technical study.Flourishing coping against natural disasters is difficult to achieve in a situation of small efficiency, staled financial development, not having access to industrious possessions, deficiency of economic reserves and safety nets in place, and broad difference of opinion crossways geographic, financial, or tribal lines. Lack of health conveniences, remoteness and low rate of education may also complex these susceptibility. Consequently, the covariate life of various natural hazards and the policy-tempted macro circumstances upsetting the rate and likelihood of effectively coping with them might reflect unreliable welfare shocks across region and sub-region leve ls.At last, societies can make worsened these natural, site and practice-specific aspects through not making any investment in substantial and communal infrastructure at the household and district level (roads and bridges). In case of rural areas, these deficiencies can be multifaceted by a high frequency of hazards because of being covered hazard-prone areas, extending the vulnerability of families to experience any losses.Although the impact a natural disaster is an outside factor, susceptibility of causes, making the shock of the event high or low, is not. Susceptibility to natural hazards is a composite subject, as it is determined by the monetary model, the phase of growth, current social and fiscal situation, coping means, risk evaluation, rate of recurrence and greatness of hazards, etc.Lindell and Prater (2003) summarize the significance of shaping the impact and the influenced agents in natural hazards. First, that information is helpful for policy makers, as they can recog nize the need for outside support and which may be extra effectual. Second, exact sections of affected can be recognized, e.g. how short income families are influenced, uniqueness of regions etc and third, it may be also helpful for setting up backing for natural hazards and the possible penalty. They also summarize how the impact of natural hazards should consider other means.One of the main questions concerning the impact of natural hazards on families or towns is how accidental they may be. Donner (2007) examined the effects of hurricanes in the US and figured out that the effects are not accidental, because some aspects such as ecological, society, demographic, and scientific, have an occurrence on the impact of such events. On the whole the flow of impact of natural hazards can be sketched as in Figure 1.figure1.PNGFigure 1. baffle of Disaster ImpactOther aspect is how establishment have defined practices concerning natural events and how they systematize help in the outcome c an also be determining(prenominal) of the crash. Such as, Peacok and Girard (1997) explain how the revitalization process after tornado in Florida was determined more by governmental obstructions rather than lack of resources.expressage Literature is available which studies the quantitative relationship between the economy and the natural disasters. Zarrar et al (2009) studied the impact of natural disasters on the Irans Gross domestic product. They adopted a auto regressive distributed Lag model in order to study the impact. The findings showed that natural disasters have negative impact on the GDP per capita and on Per captia investment. The result of the model test was that investment had a positive impact on the economy while negative impact on GDP from the indemnity from the loss of Physical capital.Macro economic variables determine the impact of these natural disasters on the long run economic growth. Aaron (2007) found that financial crises caused by these disasters lesse ned the long run growth through inflation. This inflation is the result of increased debt burden. Other reason for this inflation could be that central bank print excess notes to pay the external and internal debt. Also the tax collection is also affected which hurdles the government efforts in compensating the losses. However the loss in gross is compensated by the help of the Loans and aid given by the international institutions. They include the World Bank, International Monetary Fund and the European Union. These loans and aid influence the economic growth in the short as well as the in the long run.Pelling (2002) in his work identified that the most important macroeconomic impact of natural disaster can be studied by examining the inflation trends in the economy. More over the public expenditures by the government and the aid flowing as foreign direct investment influences the GDP growth rate. The used a comparative analysis technique of comparing different case studies to det ermine the macro-economic effects. These effects are measured by plotting the trends in GDP against macro economic factors i.e Inflation ,FDI and Loans.The literature review discusses the direct and indirect impact of economic variables on the economy. However in this research work only the impact of macro economic variables is studied.From the support of Literature review the macro economic variables which can be used to measure the quantitative impact of natural disasters on the GDP growth of Pakistan are Inflation, Internal and external debts, Foreign wait on and foreign direct investment flowing in the country.In next section of research we will take into account the above macroeconomic variables with the conclusion of concluding the impact of natural disasters on the economy of Pakistan.Methodology investigate TypeIn order to identify the macroeconomic effects of disasters, we suggest comparing a counterfactual situation ex-post to the observed state of the system ex-post. Th is involves assessing the potential trajectory (projected unaffected economy without disaster) versus the observed state of the economy. This contrasts with observing economic act post-event and actual performance pre-event, as usually done in similar analysis. Our analysis requires projecting economic development into a future without an event. In short, the type of research would be purely Quantitative.Sources of DataOur two main sources of Data areThe open-source EMDAT disaster database (CRED, 2008) maintained by the Centre for Research on the Epidemiology of Disasters at the Universit Catholique de Louvain.The proprietary Munich Re NatCat run database.Data type and Research PeriodsOur sample consists of all major natural disaster events during 1950-2010. The sample is based on information from two databases and was compiled by Okuyama (2009) with the threshold for a large event defined arbitrarily to a loss exceeding 1 percent of GDP.One database is the open-source EMDAT disas ter database (CRED, 2008) maintained by the Centre for Research on the Epidemiology of Disasters at the Universit Catholique de Louvain. Primary data are compiled for various purposes, such as informing relief and reconstruction requirements internationally or nationally, and data are generally collected from various sources and, including UN agencies, non-governmental organizations, insurance companies, research institutes and press agencies. The other database is the proprietary Munich Re NatCat Service database, which mainly serves to inform insurance and reinsurance pricing. We focus on the monetary losses.In both datasets, loss data follow no uniform definition and are collected for different purposes such as assessing donor needs for relief and reconstruction, assessing potential impacts on economic aggregates and defining insurance losses. We distinguish between sudden and slow onset events. Key sudden-onset events are extreme geotectonic events (earthquakes, volcanic eruptio ns, slow mass movements) and extreme weather events such as tropical cyclones, floods and winter storms. Slow-onset natural disasters are either of a periodically recurrent or permanent nature these are droughts and desertification.We broadly associate the loss data with asset losses, i.e. restoration to produced capital. This is a simplification, as indirect impacts, such as business interruption, may also be factored into the data. Yet, generally, at least for the sudden onset events, analysts generally equate the data with asset losses, and an indication that this assumption can be maintained is the fact that loss data are usually relatively quickly available after a catastrophe, which indicates that flow impacts emanating over months to years are usually not considered. Losses are compared to estimates of capital stock from Sanderson and Striessnig (2009), which estimated stocks using the perpetual muniment method based on Penn World table information on investments starting i n 1900 and assuming annual growth and depreciation of 4 percent. notional Framework and variables under considerationTheoretical Framework to be used in this essay to explain economical Impacts on Pakistan due to Natural Disasters. economic ImpactsGDPExposureSocioeconomic SusceptibilityDirect RisksProduced ResourcesEnvironment ResourcesHuman ResourcesType of HazardPhysical SusceptibilityRisk directionThe literature on the monetary impacts explained can be associated with framework above.Independent VariablesIndependent Determinants of such impacts and dangers can be renowned asHazard VariableThis variable is related to the type of Natural disaster/Hazard that jolts any part of Pakistan.ExposureThis variable deals with the geographical area and spatial scale of impact from the particular disaster.Economical StructureThis variable deals with the overall structure of the economy in the country and in particular region affected by the disaster (if needed).DevelopmentThis determinant d eals with risks that might directly or indirectly affect the stage of the development of the country.Socioeconomic EnvironmentIt is related to the current socioeconomic conditions in the country.Risk ManagementThis takes care of the availability of formal and informal mechanisms to share risks in a particular part of the country.The last four variables are related to economic susceptibility.Research HypothesisH0 Natural Disasters do not have any significant negative follow-on effects on the economy of Pakistan.H1 Natural Disasters do have significant negative follow-on effects on the economy of Pakistan.TechniquesWe use autoregressive integrated moving average models, also called ARIMA (p,d,q) (Box and Jenkins, 1976) for forecasting GDP into the future after the disaster event. ARIMA theoretical account approaches are chosen because they are sufficiently general to handle virtually all empirically observed patterns and often used for GDP forecasting (see for example Abeysinghe and Rajaguru, 2004). While such a type of modeling may be criticized for its black box approach (Makridakis and Wheelwright, 1989), it here serves well due to the large number of projections to be made and the difficulty identifying suitable economic model approaches.The ARIMA processRecall, an autoregressive process of order AR (p) can be defined asx t = 1x t1 + 2x t2 ++ px tp + tA moving-average process of order MA (q) may be written asxt = t +1 t1 + 2 t2 ++ q tqand an ARMA(p,q) process, with p autoregressive and q moving average monetary value can be defined to bext =1xt1 ++ p xt p + t +1 t1 ++ q tqWhere and are parameters to be estimated and are white noise stochastic error terms. Now, let yt be a non-stationary series and define the first order regular difference of yt asyt = yt yt1or more generally using a back-shift operator denoted as Bk zt = ztkyt B d yt d = (1 )An ARIMA (p,d,q) model can then be expressed asyt q B t B B d p ( )(1 ) = ( )withB p p (B) = 11B pandBq q (B ) = 11B qData AnalysisThe Box-Jenkins methodology (Box and Jenkins, 1976) is applied for determining the components of the ARIMA process i.e. we test different ARIMA(p,d,q) models with p and q to be smaller or equal 4 (due to the limited amount of data) and estimate and using Maximum likelihood techniques and the Akaike Information Criterion (AIC) as well as diagnostic checks to detect a suitable model. The data requirements were set thus that at least 5 observed data points are needed for projections into the future. This is the smallest number of observations which are needed to estimate ARIMA (4,1,4) models (however, the majority of the sample (greater 90 percent) has at least 10 data points).Furthermore, all models are tested to be stationary (usually d=1 suffices to checker a stationary process) and all series are demeaned. To include uncertainty in the projections, also 95 percent confidence forecasts were calculated and analyzed. Forecasts into the future are performed wi th the selected models and then compared to the observed variables. Increases or decreases of GDP in future years are measured as a percentage increase or decrease to baseline GDP (i.e., baseline =100) which is defined to be GDP a year before the disaster event.Furthermore, the differences between observed values and projected ones are calculated and called Diff(t), which indicates the percentage difference between the observed and projected value of GDP in year t. We focus on projections with a medium term perspective (up to 5 years into the future). This limitation is due to important data constraints for the ARIMA models within