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Some Remarks on the Estimation of Informal Economy in the Republic of Macedonia | International Journal of Scientific Research and Management

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Some Remarks on theInterpretationof Informal Economy in the Republic of Macedonia | International Journal of Scientific Research and Management Quick jump to page content Main Navigation Main Content Sidebar e-ISSN : 2321-3418 | Email: editor@ijsrm.in Register Login Home About About the Journal Editorial Team Submissions Current Issue Archives Contact Home Archives Vol 6 No 09 (2018) Economics and Management Total : PDF: 30 XML: 0 | Total views: 30 Some Remarks on theInterpretationof Informal Economy in the Republic of Macedonia Dashmir Asani, × Dashmir Asani PhD student, Department of Informatics and Statistics, Faculty of Economy, University of Tirana, Albania . Close Dode Prenga, × Dode Prenga Department of Physics, Faculty of Natural Sciences, University of Tirana, Albania . Close Elmira Kushta, × Elmira Kushta Department of Mathematics, Faculty of Technical Sciences, University “Ismail Qemali”, Vlora, Albania . Close ArticleStagePublished : 5 September 2018 | Page No.: EM-2018-667-675 | Google Scholar DOI https://doi.org/10.18535/ijsrm/v6i9.em02 Article Text Article Info Citation Tools Article Metrics Abstract In this paper we discuss some findings on the interpretation of the informal economy in a particular economical system, the Republic of Macedonia. We observed that undeviating using of standard models could produce variegated results and therefore some preliminary precaution has been taken. Therefore, by performing step by step wringer we conclude in winning values and in the evidencing of dominant factors that simulate informal economy. The work reveals the importance of model’s theorizing fulfilling in the specimen of economic systems where observables are non-stationary and the economy itself is typically in dynamical evolution. As result of such resurgence of the procedure we obtained that the country’s informal economy is going slight lanugo starting from a local peak value touched in 2010-2011. By now it is stabilized virtually the values 33%-35% of GDP. We obtained herein that the majority of economic and political measures undertaken recently in the framework of informality reduction have worked in the aimed direction. From the factors point of view we obtained that contribution of some variables in the informal economy growth in the period analyzed 1. Introduction Informal economy is specified as part of a country’s economy that is not observable in the sense of state fiscal activities. In a increasingly detailed discussion [ [1] ], [ [2] ] this definition is reserved only for the part of unregistered economy that is created as result of evading formal official records to simply escape the Taxes’ duties. There is flipside part of unregistered economy that could originate from criminal activities [ [3] ] which is expected to have variegated structure. A increasingly unstipulated concept for those unregistered economical activates is encapsulated in the definition “shadow or underground economy”. In the wringer of the informal economy there are two major objectives: interpretation of the size and identification of factors that rationalization it to exits. In this view, researchers have evidenced the fact that the un-registered is tractable however, and therefore it can be unscientific making use some theoretical relationship with its indicators. Moreover, factors and causes of informality can be analyzed in this process too. In econometrics it is believed that the existence of informal economy causes discrepancies, distortions for many economic parameters as compared to their expected values. So, it might rationalization a part unemployment gravity to be concealed, can rationalization the consumption to be higher than production or the money in diffusion to be larger than expected. Accordingly this unseen economic quantity has been modeled and unscientific [ [1] ], [ [2] ] etc., by simple regression techniques..Uncontrivedand indirect methods have been proposed but each one has its advantages and disadvantages.[ [1] ], [ [4] ] Practical evidences show that obtaining an towardly model and fixing the set for variables in each one of them depends on touchable economy under study as seen ne [ [5] ], [ [6] ], [ [7] ] an many others considerations. If data records fulfill some necessary requirements, the first vestige and the easiest way to estimate the informal economy is considered the method of “the GDP discrepancy”. It states that the difference between GDP calculated by consumption and incomes requite the informal economy GDPInformal  GDPExpenditures  GDPIncomes (1) In the reference[ [1] ] it is highlighted that results of the equation (1) would be open-door if data used in it would have been recorded thoughtfully and without any subjective distortion. Therein is noticed that usually it didn’t happen, therefore when using (1) the error should not be neglected. Other discrepancies methods based on physical outputs do need then unobjectionable databases. Nevertheless, some of those methods are complicated and their techniques of numbering seem to be questionable in some hair-trigger point of view. But in any sense, discrepancies have been largely considered as indirect indicators and traces of the Informal economy and therefore they have been undisputed as the understructure of uncontrived numbering of the informal economy. In this category have been listed discrepancy of unemployment rate, electricity use etc.[ [1] ],[ [3] ] etc. Aside those uncontrived methods, some indirect techniques have been found increasingly useful. So using simple currency ratio (SCR) by simple formula.[ [2] ] C  f D (2) where C and D are respectively the currency in diffusion and the Deposits, indices i and f stand for “informal” and “formal” whereas The numbering equal (2) is straightforward and is detailed in[ [1] ] etc. The conviction of the interpretation (2) depends on two elements: the stationary of the series which we discussed expressly in [ [8] ] and the rigorousness of the theorizing that in very economy velocities of the money in formal and informal sector are equal. Moreover the problems of zero informality time as by uncontrived modeling in[ [1] ] would mostly stupefy the numbering in the specimen of transitory economies. Next, flipside technique tabbed the currency demand tideway (CDA) with pursuit formulae or its derivative have been used largely: in (3) Here M is narrow/broad money, C the money in circulation, Tax is the stereotype tax rate and R is the interest rate for Deposits.Theninformal economy is supposed to be proportional to the extended demand for money and therefore the theorizing of equal money velocity is taken as true. In applications (1), (2) and other similar, the informal economy is modeled as linear form (or log linear) of some factors (cause variables). Generally speaking, if a candidate-factor included in the forms (1), (2) etc., has a good regression statistics, one agrees that it is a rationalization for informal economy. A increasingly ramified method but probability increasingly constructive is the MIMIC model that put the informal economy in the middle point between factors and indicators. It looks like pursuit (4) where in IndicatorY could be placed any macroeconomic alphabetize areas in FactorX could be whichever economic parameter or variable. In general, factors are parameters like Taxes, tariffs, the incomes, wages, contributions, a quantifier of the structure of the wanted for the country, political performance, and many others. Informal or shadow economy plays the role of the intermediate transcript between sides of relation (4), starting as response variable for the set of factors, and rhadamanthine factor variable for final indicators. Therefore a double regression is needed in this specimen which inevitably needs for increasingly shielding procedures as have been ripened in [ [9] ], [ [10] ] etc.Theoreticallythe mathematical nature of the series of variables is expected to stupefy the estimation. This speciality is taken into consideration in our calculation. Finally, flipside source of incertitude in the evaluation of the latent variable under viewing is related to the real structure of the unregistered economy. So, the presence of criminal or similar activities that contribute in the shadow economy is inevitable and this last cannot be modeled so the overall numbering became complicated [ [11] ]. As a result, by uncontrived implementation of the standard modeling it is untrusty that values obtained could not be unchangingly satisfactory or plane realistic. Based on those remarks, we have predictable the applications of linear models mentioned herein by analyzing each element discussed in this introduction. 2. Some findings using uncontrived and indirect methods The economy of Republic of Macedonia has known an energetic transpiration at 1990 when the system has been transformed toward the market economy. In this sense it is expected that the variables representing economic observables have been highly dynamical during the succeeding period. We commented this full-length in our recent work.[ [8] ] We unclose that during [1990, 2016], methodical resurgence in public database have been unromantic consecutively until a full modernized methodology has been unexplored by the end of 2010.[ [12] ],[ [13] ] In this view we expected that linear modeling of the informal economy might have considerable incertitude or other incompatibilities due the lack of fulfilling of some assumptions. In our first numbering we observed that the literally using of standard models leads to variegated results. From the other side, it happen that an observable that does not towards as factor in the regressions of the type (3) or (4), has been identified as related with informal economy calculated using flipside model. Hence we addressed them in the followings. 2.1. Avoiding premature conclusions using variegated tideway The interpretation of the informal economy for the Republic of Macedonia up to 2008 has been reported consecutively as seen in[ [13] ],[ [14] ] or in a increasingly unstipulated view as in.[ [15] ] In our work we considered the evaluation of this parameter for a narrow period of time specified as [2004, 2016]. Some specifics of the numbering for this period were reported in.[ [8] ] Herein, we are interested on the size of informal economy and the effect of some factors on it. We have analyzed many of them, but purposely we will discuss the self-indulgence effect on the informal economy. In this tideway we considered the numbering of the informal economy using discrepancies models and used those estimations to trammels the possible relationship between the latent variable and factor-like ones. The most highlighted finding we observed for some well-defined variables which we will discuss shortly below. When applying unemployment model of informal economy using yearly data we obtained that the result is quite similar with the interpretation using GDP discrepancies as seen in the Figure 1.a. It has the same trend as the self-indulgence alphabetize as seen in the Figure 1.b. Therefore in mechanical view, this variable is expected to influence our latent variable. In practice, there is a worldwide weighing that correlation is indicator of causative. Figure 1(a) a. Percent of Informal GDP. Orange line, equal to GDP discrepancies, undecorous line, equal to Unemployment model Figure 1 (b) b. RelativizedSelf-indulgencealphabetize (orange line ) and Informal Economy (black line) The same result is obtained in the specimen of the variable measuring legalistic performance of the government as the ratio Budget Deficit/GDP. In our wringer we commented those findings as indicators for possible relationship but increasingly proof is needed to conclude. Next we use the linear modeling of the type (3) extended as discussed in [ [16] ] and other models of type (4) using forms suggested on the literature. We obtained that the regression and the statistics for the variable “index of corruption” didn’t personize the uncontrived relationship with informal economy and therefore the upper positive correlation seen in the Figure 1 is considered as false in our case. In unstipulated this is not novel as seen in [ [17] ]. This suggested that the discrepancies method is not well-judged and should be revisited. The other possible reasons could be the nature of well-defined variable. Similar results have been obtained for the other parameter analyzed the quality (performance) economical governance. Adding to the remarks above, in this specimen we proposed to use increasingly tinny series based on quarter or plane monthly data. But from our very system perspective, we supposed that linear models would be unromantic if there is no regime transpiration in the period examined, so it would have been checked with priority. 2.2. Identification of the weightier interval where a linear model is reasonably workable We analyzed the set of variables proposed in [ [1] ] in the framework of CDA or MIMIC model. The trend of variables (logarithmic variables) showed two special points, one was located virtually 1990 and the other one in the zone [2002, 2004]. We observed that the policies of the informal economy calculated using Cagan model as given in [ [1] ] etc., unmistakably differs to the one variable that is expected to be co-linear, as the rate of unemployment or example, Figure 2.a. Using the reviewed CDA model proposed by Tanzi, we obtained the same policies which support the vestige of a strong transpiration in-betweens the years 2002-2004. Therefore, this consists in a special point that should have been avoided form the series used in linear forms as (3). Moreover, the interpretation with CDA in the full interval [1998, 2014] showed an undervaluation of informal economy, considering the level of 20% is foible for the ripened country as reported in [ [7] ] which is not our case. We thought that the major rationalization for the inconsistencies of the value of informal economy unscientific for interval [1998, 2014] as evidenced in Figure 2 was related to theoretically regime transpiration in 2002. So, a largest tactic for linear regression would have been the use of data series that do not included records from this time zone. Figure 2 (a) a. Informal Economy by Unemployment method Figure 2 (b) b. Informal economy by CDA in Tanzi version By such a correction of the reference interval we have improved the calculated the informal economy in the period [2004, 2014] as given in Figure 2.b. In this specimen we obtained a upper value of it virtually 38% of GDP near 2010-2011 and a decreasing trend form this stage as seen in the Figure 2.b. the stereotype level of informal economy has been found higher than 20% and this result has been supported by other models too. 2.3. Assessment of typical variables representing particular categories on modelsFlipsideissue has been initiated from unexpected findings for the effects of some factors. So, in numbering of the type (3) coefficient of linear regressions for some categories of Taxes were found negative that seems to be a meaningless result. In principle this is possible as discussed in the reference [ [2] ], [ [3] ] and others considering economical systems are complicated in the weightier approach, and sometimes behave as ramified in the full sense. A corollary of this property is that there is no rigid model for all cases, as is proven to be true in many applications. In such a specimen we operated equal tactics mentioned whilom to exclude “exterior troubles”. Next we extended the idea of an adaptive using of the models recommended in the literature as [ [6] ] or [ [5] ] by considering a set of variables for each category involved in equations of the type (3) or (4). Thus, we searched empirically to find which touchable variable could be exactly in the role described by the towardly category in the equation. So, in CDA model the variable “Taxes” appears in relation as ln(1+Tax.Rate) [ [1] ]; variables “Interests Rates” appears directly in equation of the type (3), other parameters towards in logarithm Figures etc. Hereto we realized a generalized regression procedure of a linear tideway for ln(C/M) including all categories of variables and all variables under examination. The series that “survive” statistical test for regressions including a satisfactory ratio of error to the stereotype value evaluated as seen in Table 1, have been qualified as the towardly term for final numbering within the model of the type (3) or (4). In the Table 1 we observed that all variables in the regressions have good pvalues, but VAT has a good error to value ratio and good statistical fitting parameters. The variable “Average Taxes” that appears in standard models of the type (3) and its Tanzi equivalents seems to be not the weightier choices. In the other side, the VAT has good statistics (pvalue is obtained lower than standard thresholds) and good error to vale ratio. Moreover, we obtained that in some regressions of type (3) the coefficient of the term ln(1+AverageTaxRate) has negative value that is theoretically wrong. The two other terms including VAT or Total Taxes have had positive sign in the regression so each one could play the role of “Taxes” in theoretical model. Taxes are expected to simulate the informal economy so the sign should be positive. In the same way we have to decide which element of the category “Interest Rate” plays the role of the Interest rate for Deposit as an expected inhibitor effect in informality in original model and so on. 2.4. Remarks for the variable of type currency The last element we addressed herein was the Indicator variable. In theory the indicator of informal economy is money aggregate. The question herein is to identify which one of them represents at the weightier the informality for the economy. Again, the uncontrived use of series has given winning values but not resulting with some expectation. The most important indicator for informal economy is the currency out of deposits [ [1] ] so we discussed it increasingly thoroughly. We considered the fact that the value of money inward in mazuma the country in the form of remittances is considerable,[ [18] ],[ [19] ] In general, those inputs are found usually in Euro currency which has been used as payment tool as well, behaving temporally as national currency itself (Denar) and therefore we proposed to use it as part of total money in diffusion by replacing C/C+R in the CDA model. Notice that by uncontrived use of models we obtained a lower than expected level of informal economy whereas if including remittances in C in has shifted up by a few percent. But the most intriguing part of these discussions comes from finding represented in the Figure 3.a where it is seen that C/D has a decreasing trend in all the period [2001, 2015] whereas it is supposed to be proportional to the informal economy. Figure 3 (a) By red line, the ratio of Currency (C)+Remittance to Deposits (D); undecorous line, C/D ratio Figure 3 (b) b. In orange, informal economy by simple Cagan model.Undecorousline, Currency +Remittances This last was not reported to show unvarying decreasing trend in this period and therefore the initially unsupportable indicator variable C/D would largest be (C+R)/D. Hereby we noticed the resurgence of the numbering but then the transpiration from year to year is high, in some specimen virtually 5% that is not theoretically supported. This last remark suggests then the use of tiniest series which we reported in.[ [8] ] 3.Numberingof informal economy for the Republic of Macedonia We have considered all precaution steps analyzed whilom in the final interpretation of the informal economy of the Republic of Macedonia. The opportune period for numbering in [1996, 2016] is considered the narrower interval [2004, 2014]. Other findings and comments considered have been reported in [ [8] ] as typical for the using of linear models, CDA, SCR or plane MIMIC in our touchable system. Next the variables stuff qualified as increasingly representative of a category related to the linear form (3) have been used in the numbering based on simple currency ration (SCR) and Currency Demand Approach. The result showed significant resurgence on the determination of major causes for informal economy in the country. Consequently we were worldly-wise to largest selection of the set of variables to be used as factors and indicators in the increasingly wide MIMIC model. We observed that those steps improved the calculation. Figure 4 (a) a. Informal Economy by MIMIC 8-1-3 model : Figure 4 (b) b. Reproduction of the indicators: yellow line, unemployment rate, undecorous line, ln(GDP); red line logarithm of narrow money, Now the latent variable showed slighter changes say virtually 1%-3% from year to year and moreover the reproduction of the indicators based in model’s parameters is obtained qualitatively good (quite correct in logarithmic scale) as seen in the Figure 4.b. Next, the full wringer of the system has been performed straightforwardly. Thus, variables as Remittances, GDP per capita, VAT, GDP deflator, Taxes over Personal Incomes, and Interest Rates of Deposits have been identified as key factor in the size of the informal economy for the country. Indicators of the informal economy were identified to be the GDP per Capita, the Narrow money M1 and the Rate of Unemployment. The unregistered economy has reached 35% of the GDP near the year 2010 and now is virtually 31-33% of the GDP. Oscillations protract to be present on the trend of the annuals value estimated, so the wringer needs for increasingly resurgence which remains to be addressed in our future works. 4. Conclusions We realized to find the most towardly time interval to implement linear modeling in the numbering of the informal economy for Republic of the Macedonia. We obtained that the set of variables that mostly influenced the informality and shadow economy could be prescribed by a step by step selecting procedure. In particular, we observed that the self-indulgence and economic performance of the government have a complicated effect, whereas Remittances, Value Added Taxes, Taxes in the Incomes, Interest of Deposits and GDP acts as a set of factors that are responsible for the size of informal economy for the period [2004,20014] . We identified GDP per Capita, the Narrow Money and the Unemployment as key indicator of the informal economy for the period exanimated. The underlined trend of informal economy for the EM-2018-673 country in the period [2004, 2014] showed the peaks at 35%-38% virtually the year 2010 and now it is decreasing toward a stationary state to the virtually 33% of the gross national production. 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[ CrossRef ] [Google Scholar] Analyzing Migration Decisions: The First Step–Whose Decisions? Sell RalphR. Demography.1983-aug. [ CrossRef ] [Google Scholar] Downloads Download data is not yet available. Comments & Peer Review Please enable JavaScript to view the comments powered by Disqus. Author's Affiliation Dashmir Asani PhD student, Department of Informatics and Statistics, Faculty of Economy, University of Tirana, Albania Google Scholar Dode Prenga Department of Physics, Faculty of Natural Sciences, University of Tirana, Albania Google Scholar Elmira Kushta Department of Mathematics, Faculty of Technical Sciences, University “Ismail Qemali”, Vlora, Albania Google Scholar Copyrights & License International Journal of Scientific Research and Management, 2018. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Article Details Issue: Vol 6 No 09 (2018) Page No.: EM-2018-667-675 Section: Economics and Management DOI: https://doi.org/10.18535/ijsrm/v6i9.em02 How to Cite Asani, D., Prenga, D., & Kushta, E. (2018). Some Remarks on theInterpretationof Informal Economy in the Republic of Macedonia. International Journal of Scientific Research and Management, 6(09), EM-2018. https://doi.org/10.18535/ijsrm/v6i9.em02IncreasinglyCitation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX HTML Viewed - 92 Times PDF Downloaded - 30 Times XML Downloaded - 0 Times Sections PDF XML Downloads PDF XML Sections We Recommend Latest Article About Us International Journal of Scientific Research and Management is , unshut access, peer reviewed, monthly journals publisher We believe in publication values and request all the authors for same. 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