Despite the hugely impressive positive outlook of a peaceful election, the study found that there were a number of election risks factors that could trigger violence during the governorship election in the state if not mitigated.  Such factors, in their order of rating by the respondents, include a) Exclusion and Discrimination against the youth (83%); b) Religious Extremist, Cultist and Other Armed groups (73%); c) Undue influence of Money and god fathers (82%); d) Partiality of INEC (76.2%); e) Partiality of security Agents (80%), Delays in the handling of pre-election cases (68%); and f) Broadcast and publishing of Hatred (71.8%). These are the most critical factors that could trigger violence in the governorship election, each with an aggregate score of above 83%.<\/p>\n\n\n\n

Other electoral risk factors identified include drug Abuse (84%), Ambiguous Electoral Laws (78%), Disenchantment with the Electoral process (82%), Hate speeches (86%), Interethnic\/religious\/communal conflicts (68%), Illegal immigrants (77%), and Nature of of politicking in the state (84%) (Troublesome Politicians, Political Parties, Leaders, and candidates).<\/p>\n\n\n\n

B. Actors likely to cause Electoral violence in each state<\/h1>\n\n\n\n

The roles of some actors were also found to be critical to the peacefulness or otherwise of the election. In their order of magnitude, the three most critical actors identified as posing some risks of violence to the election are a) Religious extremists\/cultists\/armed groups (73%); and b) security agencies (70%) and Vigilante groups (68%) with an average score above 70%. <\/p>\n\n\n\n

Others with identified with moderate potential of causing violence in the election include Political parties (65%), INEC (62%), Party thugs (61%) and Insurgents (61%). <\/p>\n\n\n\n

The study also highlighted the specific risk factors associated with each of these key actors. They are as follows:<\/p>\n\n\n\n

Political Parties:<\/strong> The risk factors identified in their order of significance are: a) Lack of training and corruption of party Agents (79%); b) Lack of transparency and disagreement over the selection of party officials and candidates (78%); c) Disorderly party rallies, processions and campaigns (75%); d) defection and carpet crossing (68%); e) Contentious Party Primaries and meetings (63%); f) Lack of respect for party rules (62%); <\/p>\n\n\n\n

INEC: <\/strong>For INEC, the most pertinent risk factors identified by the study in their order of significance include: i) Partiality of INEC Officials (82%); ii) Problem of Underage Registration (73%); iii) Problems associated with the continuous Voter Registration exercise (69%); iv) Failure to prosecute Electoral Offenders (68%); v) Poor voter Education by INEC (65%); and vi) substitution of Trained Electoral Officials (64%).<\/p>\n\n\n\n

Security Agencies:<\/strong> Security agencies emerged as the actor with the highest level of threats to the election. The most influential risk factors identified here, also in their order of importance, include:<\/p>\n\n\n\n

i) Partiality of Security Agents (80%); ii) Low Sense of Safety Among members of the Public (Banditry, Kidnapping, Assassinations, etc.) (80%0; iii) Lack of Synergy between INEC and Security Agents (79%); iv) Poor Training and low Professionalism of Security Agents (78%); v) Lack of Synergy Among Security Agents (76%); vi) Problems Associated with the Deployment of Security Agents (75%); vii) Inadequate or excessive presence of Security Agents (74%); and viii) Aggressive and Excessive use of Force (72%). Evidently, all the identified risk factors but one ranked above 70%. This shows that special attention must be paid to the roles and activities of security agents throughout the electoral cycle.<\/p>\n\n\n\n

The Judiciary: <\/strong>Regarding or in considering the role of the Judiciary to Election Violence in Kogi, the study reveals the following are most likely to lead to violence in the upcoming elections: i) Delays in the Handling of Pre-election cases (68%); ii) Confusing and Contradictory Court decisions (65%); iii) Partiality of the Judiciary (64%); iv) Capacity of the Judiciary (Including Inadequate of Judges) (59%); and lastly, v) Corruption and integrity of the Judiciary (54%).With these ratings, the judiciary would appear to be the actor with the lowest risk to the governorship election.<\/p>\n\n\n\n

The Media:<\/strong> Lastly, assessing the role of the Media and Electoral violence in Kogi elections, the study reveals as follows: i) Broadcast and Publishing of hatred (76%); ii) Misinformation of the Public by the Media (72%); iii) Failure of Registration Bodies to ensure adherence to established Rules by the Media (69%); iv) Abuse of Social Media (64%); and v) Sensationalism and Provocation by the Media (63%).  From these findings, the media also pose some measure of risks to the governorship election. It is arguably the next to security agents in terms of the weight ascribed to the risk factors.<\/p>\n\n\n\n

C. Other Critical Electoral Risk Factors in Kogi State<\/h1>\n\n\n\n

The analysis also revealed some other critical electoral risk factors in the state based on the understanding of experts drawing across the academics, security agencies, mass media, etc. These factors include the following in their order of ranking: a) corruption among party officials (79%); b) political interference in the work of INEC (77%); c) the presence of strong opposition (73%);<\/p>\n\n\n\n

d) inadequate training and conduct of party agents (79%); e) adherence to process and procedures (90.4%); f) proliferation of small arms and light weapons (78%); g) inadequate training and conduct of security agents (72%); and i) abuse of power of incumbency (70%).<\/p>\n\n\n\n

Other factors include INEC\u2019s information management (73%), relationships among federal, state and local governments (71%), legislative-executive relations at federal level (69%), involvement of informal political groups (61%), funding of elections (69%), problems associated with the recruitment and payment of election workers\/adhoc staff (59%), reliability of election equipments (53%), and foreign interests and interference, including election observers (52%).All the risk factors were almost equally rated across the Eleven (11) LGAs of the state.<\/p>\n\n\n\n

D. Overall Outlook of the Election<\/h1>\n\n\n\n

The outlook for a peaceful election was generally impressive. Specifically, (66%) of the respondents across the state expected the election to be peaceful. However, (17%) of the respondents expected the election to go the other way round. The other (17%) were undecided. When further interrogated about the expectation of the election, most of the respondents maintained their earlier position in terms of expectation of a peaceful election, though with a slight drop in the level of expectations of a peaceful election. Specifically, (51%) expected the election to either be \u2018peaceful\u2019 or \u2018very peaceful\u2019. However, (12%) of the respondents expected the election to be violent. The remaining (37%) were undecided. This shows some reasonable measure of consistency in the patter of responses to the first and the last questions on the survey instrument. Based on this popular perception, the Kogi governorship election should be largely peaceful, particularly in the West Senatorial districts and in large parts of the Central Senatorial districts.<\/p>\n\n\n\n

Table 1: Expectation of a peaceful election in the state (%)<\/h1>\n\n\n\n

<\/td>	1. Do you agree that election in this area will be peaceful?<\/strong><\/td><\/tr>
<\/strong><\/td>	<\/td>	Frequency<\/strong><\/td>	Percent<\/strong><\/td>	Valid Percent<\/strong><\/td>	Cumulative Percent<\/strong><\/td><\/tr>
Valid<\/strong><\/td>	agree<\/strong><\/td>	259<\/strong><\/td>	27.9<\/strong><\/td>	27.9<\/strong><\/td>	27.9<\/strong><\/td><\/tr>
disagree<\/strong><\/td>	94<\/strong><\/td>	10.1<\/strong><\/td>	10.1<\/strong><\/td>	38.0<\/strong><\/td><\/tr>
Strongly agree<\/strong><\/td>	357<\/strong><\/td>	38.5<\/strong><\/td>	38.5<\/strong><\/td>	76.5<\/strong><\/td><\/tr>
Strongly disagree<\/strong><\/td>	66<\/strong><\/td>	7.1<\/strong><\/td>	7.1<\/strong><\/td>	83.6<\/strong><\/td><\/tr>
undecided<\/strong><\/td>	152<\/strong><\/td>	16.4<\/strong><\/td>	16.4<\/strong><\/td>	100.0<\/strong><\/td><\/tr>
Total<\/strong><\/td>	928<\/strong><\/td>	100.0<\/strong><\/td>	100.0<\/strong><\/td>	<\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n Table 2: Outcome of election in the state (%)<\/h1>\n\n\n\n  <\/td> 69. On the whole, how do you think that this election will go?<\/strong><\/td><\/tr>  <\/strong><\/td>  <\/td> Frequency<\/strong><\/td> Percent<\/strong><\/td> Valid Percent<\/strong><\/td> Cumulative Percent<\/strong><\/td><\/tr> Valid<\/strong><\/td> Not Sure<\/strong><\/td> 343<\/strong><\/td> 37.0<\/strong><\/td> 37.0<\/strong><\/td> 37.0<\/strong><\/td><\/tr> Peaceful<\/strong><\/td> 255<\/strong><\/td> 27.5<\/strong><\/td> 27.5<\/strong><\/td> 64.4<\/strong><\/td><\/tr> Very Peaceful<\/strong><\/td> 221<\/strong><\/td> 23.8<\/strong><\/td> 23.8<\/strong><\/td> 88.3<\/strong><\/td><\/tr> Very Violent<\/strong><\/td> 53<\/strong><\/td> 5.7<\/strong><\/td> 5.7<\/strong><\/td> 94.0<\/strong><\/td><\/tr> Violent<\/strong><\/td> 56<\/strong><\/td> 6.0<\/strong><\/td> 6.0<\/strong><\/td> 100.0<\/strong><\/td><\/tr> Total<\/strong><\/td> 928<\/strong><\/td> 100.0<\/strong><\/td> 100.0<\/strong><\/td>  <\/strong><\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n As Table one (1) indicates, some measure of consistency is noticeable. The decline in the expectations of peaceful election expressed in question 69 is expected. At that point, respondents had gone through all the questions and would have had their expectations mediated by the contents and substance of the intervening questions.<\/p>\n\n\n\n There were, however, discrepancies across the Twelve (12) out of Seventeen (17) LGAs effectively covered in the state. With respect to the first question, expectations of a peaceful elections were rated over 60% in Twelve (12) of the LGAs, with only Ogori Magongo and kogi standing at 87% and 28% respectively. However, the positive ranking fluctuated up and down with respect to Q69. Specifically, level of expectations remains positive in above 50% rating in Eight  (8) of the LGAs, namely Bassa, Dekina, Igalamela; Kogi, Ofu, Ogori Magongo, Omala, and Yagba West. While a downward trend was noticeable across these Nine LGAs, Kogi was exceptional, rising from 28% in Q1 to 52% in Q69. Again, the decline in Ibaji, Idah, Ijumu, and Mopamoru were too sharp, falling from 68% in Q1 to 0% in Q69. <\/p>\n\n\n\n 1. Table 3: Expectations of a Violent Election by LGAs (%)<\/h1>\n\n\n\n LGAs<\/strong><\/td> Q1<\/strong><\/td> Q69 <\/strong><\/td> Risk Level Status (Average of Q1 & Q69)<\/strong> Key: 0-9%(Green), 10-19%(Amber), 20% and above(Red)<\/strong><\/td><\/tr> Adavi<\/td> 15.5<\/td> 0<\/td> 7.75<\/td><\/tr> Bassa<\/td> 36.7<\/td> 5.0<\/td> 13.9<\/td><\/tr> Dekina<\/td> 20<\/td> 18.6<\/td> 9.65<\/td><\/tr> Ibaji<\/td> 3.3<\/td> 0<\/td> 3.3<\/td><\/tr> Idah<\/td> 0<\/td> 83.3<\/td> 83.3<\/td><\/tr> Igalamela Odolu<\/td> 31.3<\/td> 26.6<\/td> 28.95<\/td><\/tr> Ijumu<\/td> 23.8<\/td> 20.4<\/td> 11.05<\/td><\/tr> Kabba Bunu<\/td> 3.5<\/td> 2.3<\/td> 2.9<\/td><\/tr> Kogi<\/td> 48.0<\/td> 0<\/td> 24<\/td><\/tr> Lokoja<\/td> 0<\/td> 0<\/td> 0<\/td><\/tr> Mopamuro<\/td> 11.9<\/td> 0<\/td> 11.9<\/td><\/tr> Ofu<\/td> 14.9<\/td> 33.3<\/td> 12.05<\/td><\/tr> Ogori\/Magong o<\/td> 11.7<\/td> 3.9<\/td> 5.2<\/td><\/tr> Okene<\/td> 13.3<\/td> 11.5<\/td> 12.4<\/td><\/tr> Omala<\/td> 13.5<\/td> 9.9<\/td> 7.8<\/td><\/tr> Yagba East<\/td> 13..4<\/td> 12.5<\/td> 6.48<\/td><\/tr> Yagba West<\/td> 19.6<\/td> 9.9<\/td> 7.37<\/td><\/tr> Olamaboro<\/td>  <\/td>  <\/td> Data missing<\/td><\/tr> Ankpa<\/td>  <\/td>  <\/td> Not covered<\/td><\/tr> Okehi<\/td>  <\/td>  <\/td> Not covered<\/td><\/tr> Ajaokuta<\/td>  <\/td>  <\/td> Not covered<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n As can be gleaned from Table 3, the data suggests the prospects of a very peaceful election in Eight (8) LGAs. These are Adavi, Ibaji, Kabba Bonu, Lokoja, Ogori\/Magongo, Omala, Yagba East and Yagba West. While moderately peaceful election with a high risk of violence are in Six other LGAs. These are Bassa (13), Dekina (9), Ijumu (11), Mopamoru (12), Ofu (12), and Okene (12); and The most violent election are in three (3) LGAs, namely Idah, Igala mela, and Kogi.<\/p>\n\n\n\n Overall, the data above suggest the prospects of a peaceful election in two senatorial districts of the state (West and central) of the state. These six others tend to portray a worryingly low level of expectations of a peaceful election especially Bassa, Mopamoru, Ofu, and Okene on the edge. They deserve greater attentions, alongside the most violent prone zones of the East Senatorial Districts of the state.<\/p>\n\n\n\n MAJOR FINDINGS<\/h1>\n\n\n\n The following findings, among others, were obtained from the information generated from this study:<\/p>\n\n\n\n With respect to the expectation of a peaceful election, the result of the survey shows that majority of the respondents in Kogi state are optimistic that the election will be peaceful. This highly emphasises the perceptions of respondents from Kogi Central (82%) than Kogi East and West at 60% respectively. Nevertheless, the responses on the prospect of peaceful elections show that the general political ambience with respect to peaceful conduct of the forthcoming election is very uncertain, but at best could be peaceful in all Senatorial district.<\/li> The survey reveals that hate speech could precipitate electoral violence in the state as indicated by the respondents. However, there is slight difference in the opinion of respondents in all three senatorial district, as the respondents in Kogi East and West respectively, who strongly agreed that hate speech can lead to violent election also have other contrary views who are in the slight minority group that hate speech may not lead to violence.<\/li> The study also reveals that across the state, the respondents are of the perceptions that interethnic\/religious and communal conflicts could be sources of violence during the election as indicated by majority of the respondents, while a small fraction disagreed and another little fraction of the group were undecided. This suggests that there are existing interethnic\/religious and communal conflicts in the senatorial district that may likely escalate during the elections and precipitate electoral violence. <\/li> The survey also exhibits the fact that Troublesome Politicians, Political Parties, Leaders, and Candidates are very likely to cause violence during elections in the Kogi state November, 2019 as indicated by a sum majority response of total the respondents. There is general gender vertical agreement to this perception. Majority of the respondents across the three senatorial district agree that troublesome politicians, political parties, leaders and candidates are likely to cause electoral violence in the state.<\/li> The study revealed that majority of the respondents hold the view that widespread availability and use of hard drugs could precipitate electoral violence in the state November 2019 election. This opinion is also held by gender respondents. Kogi Central and East senatorial districts topped states where the widespread use and abuse of hard drugs is noticeable and expressed, which could influence electoral violence in the state. <\/li> There is expressed overall disenchantment with the government as well as with the electoral process that could lead to electoral violence in the state November elections as indicated by majority of the respondents and some very few disagreements while only a tiny fraction were undecided. This view is shared by majority of the respondents irrespective of gender, and senatorial district and locality. The Kogi state respondents believe that citizen disaffection with the electoral process could result in electoral violence by number, especially around the issues of non-payments of salary arreas.<\/li> The groups that have the most likelihood of causing electoral violence are, political party thugs, political parties, insurgents, religious extremists, security agencies, and cultists and other armed groups, while the pan-ethnic groups and civil society organisations respectively were considered by respondents as a group that is less likely to constitute threat to electoral violence.<\/li> In relation to party politics, the survey shows that several factors such as influence of money and godfathers, disorderly party rallies, contentious party conventions, lack of respect for party rules, lack of training and corruption of party agents, and defections, among others, can cause electoral violence for Kogi state. However, “undue influence of money and godfathers” was listed as the topmost causative factors of electoral violence. <\/li> In relation to election management, the problems with the distribution, location and adequacy of polling units; partiality of INEC officials; movement and distributions of election materials; INECs overall preparedness; poor voter education by INEC were some of the most pronounced management issues that respondents believe could cause electoral violence in all four states.<\/li> Findings of the study on security agencies and the likelihood of electoral violence indicates that respondents from Kogi state are in agreement that \u201cpoor training and low professionalism of security agents\u201d, \u201cpartiality of security agents\u201d, \u201cLack of synergy between INEC and security agents\u201d, \u201clow sense of safety among members of the public\u201d  and \u201clack of synergy among security agencies\u201d are more likely to cause violence during elections in the states than any other actions associated with security agents. More respondents from Kogi East than any of the other two district are of the view that partiality of security agents and aggressive or excessive use of force are more likely to cause violence during elections.<\/li> In terms of the actions of the judiciary leading to electoral violence especially, the study threw-up concerns in the order presented as arising from corruption and integrity of the judiciary; capacity of the judiciary; confusing and contradictory court decisions; partiality of the judiciary; and delays in the handling of pre-election cases. <\/li> The survey reveals that the media can contribute to the outbreak of electoral violence in the state, and this would be the case if the media is implicated in issues such as misinformation of the public, broadcast and publishing of hatred; partisanship, favouritism and partiality; failure of regulatory bodies to ensure adherence to established rules; sensationalism and provocation; lack of professionalism and finally Abuse of social media and unequal access to media.<\/li><\/ol>\n\n\n\n Background of the study<\/strong><\/li><\/ol>\n\n\n\n Constitution of the Federal Republic of Nigeria specifically states that \u201cThe security and welfare of the people shall be the primary purpose of government\u201d <\/p>\n\n\n\n The main concept behind the formation of a state is security. Life by nature, according to Thomas Hobbes, was brutish, nasty, delicate and cruel. Every man competes for survival. The rule of Life then was survival of the fittest. The state thereby existed to ensure that there is a peaceful co-existence among the people as every individual now has the liberty to acquire property and live freely with a central body (the state) regulating the affairs of man. The state therefore has the responsibility of maintaining law and order in the society and also to protect and defend the national integrity of the state. In recognition of the above, the 1999<\/p>\n\n\n\n It appears government has failed to provide a secured and safe environment for lives, properties and the conduct of economic activities. The rate of increase in criminal activities in Nigeria is alarming. Since the country returned to democratic rule, security of life and property has been so threatened, armed robbery, terrorism and other related crimes is on the increase. This has resulted to high number of casualties on Nigerians and non Nigerians as well as unpalatable consequences for the nation\u201fs economic growth and development.<\/p>\n\n\n\n In an attempt to fight the increasing waves of violent crime in Nigeria, the federal government has enacted the Anti-Terrorism Act of 2011, strengthened the Ministry of Defense with huge allocation of fund to fight insecurity in the 2013 and 2014 budget. For example, the National Assemble recently approved a loan of One Billion US Dollar (US$IBn) to fight terrorism. <\/p>\n\n\n\n All these monies were meant to purchase fighting equipment and organized special training for the security forces.  The National Security Adviser (NSA) has organized several training programmes both local and international. Despite these, it appears the level of violent crime in the country is still high, and a confirmation of this is the low ranking of Nigeria in the Global Peace Index and the declaration of Nigeria as a terrorist Nation by US. <\/p>\n\n\n\n 1.3 Objectives of the study<\/p>\n\n\n\n 1. To explore the conceptual analysis of crime and insecurity facing our beloved country \u2013Nigeria with emphasis to violent crime<\/p>\n\n\n\n 2. To explored the proximate causes of violent crimes, its implications on the socio \u2013 economic development of the country,<\/p>\n\n\n\n  3. To identify the challenges facing the securities agencies<\/p>\n\n\n\n 4. To make recommendations that will assist the society in curbing the rising violent crime in Nigeria.<\/p>\n\n\n\n 1.4 Research Questions<\/strong><\/p>\n\n\n\n 1. What are the causes of crime and insecurity facing our beloved country \u2013Nigeria with emphasis to violent crime<\/p>\n\n\n\n 2. What are the implications of violent crimes on the socio \u2013 economic development of the country,<\/p>\n\n\n\n  3. What are the challenges facing the securities agencies<\/p>\n\n\n\n 1.5 Research Hypothesis<\/p>\n\n\n\n H0: Social crime does not have a significant effect on socio-economic development of kogi eas senatorial district of kogi state<\/p>\n\n\n\n H1: Social crime have a significant effect on socio-economic development of kogi east senatorial district of kogi state<\/p>\n\n\n\n H02: There is no relationship between social crime and socio-economic development<\/p>\n\n\n\n H2: There is a relationship between social crime and socio-economic development<\/p>\n\n\n\n 1.6 Definition of terms<\/p>\n\n\n\n Societal crime: Societal crime is defined as the total number of crimes committed by members of the society, or as the rate of these crimes. … Other senses of the concept could be envisioned, such as the harm that these crimes cause to society. However, there are reasons to use the concept as defined here.<\/p>\n\n\n\n Terrorism: The unlawful use of violence and intimidation, especially against civilians, in the pursuit of political aims.<\/p>\n\n\n\n Insecurity:<\/p>\n\n\n\n Insecurity is a feeling of inadequacy (not being good enough) and uncertainty. It produces anxiety about your goals, relationships, and ability to handle certain situations. Everybody deals with insecurity from time to time<\/p>\n\n\n\n 1.7 Literature review<\/p>\n\n\n\n Theoretical literature on economic crimes and economic growth has generated a rich debate over the last few years. Scholars studying economic crimes have theorized both how economic crimes can reduce economic growth and also how it can increase economic growth. On the one hand, scholars such as Ekundayo, Obasaju, AdedoyinIsola and Iseolorunkanmi (2013), Rotimi & Obasaju (2013), Ezema and Ogujiuba (2012) and OECD (2012) have argued that economic crimes are detrimental to economic growth. They point out that economic crimes modify government goals and divert resources from public purposes to private ones, thereby resulting in deadweight loss to society. Furthermore, economic crimes may also discourage private investment by raising the cost of public administration or by generating social discontent and political unrest, which in turn, may slow economic growth. On the other hand, Colombatto (2003), Wedeman (1997) and Lui (1985) theorize that it is possible for economic crimes to be beneficial to economic growth by circumventing pervasive and inefficient regulations at low cost as well as speed up the bureaucratic process. Specifically, Wedeman (1997) observe that many corrupt countries have rapid growth rates. However, Ahmad, Ullah and Arfeen (2012) and Powell, Manish and Nair (2010) find economic crimes to be growth-enhancing at low levels of incidence and growth-reducing at high levels of incidence.<\/p>\n\n\n\n Empirical literature, for instance, the works of Mauro and Carmeci (2007), Nageri, Gunu and Falilat (2013) and Ekundayo et al (2013) have consistently reported a negative linear relationship between economic growth and economic crimes except the works of Ahmad et al (2012) and Aidt, Dutta and Sena (2008) who found non-linear relationship between economic growth and economics crimes in a panel of countries. It is, however, not certain if a non-linear relationship exists between economic crimes and economic growth in Nigeria as no empirical investigation on the relationship between economic growth and economic crimes have come to this conclusion.<\/p>\n\n\n\n The first step towards determining why economic crimes have persisted despite government\u2019s efforts to curb them lies in the determination of the nature of the relationship between economic crimes and growth of the Nigerian economy, which has left a wide gap in most empirical works reviewed. This failure to determine the nature of the relationship between economic growth and economic crimes has also affected the choice of methodology employed by previous empirical works on Nigeria. This study is an attempt to offer a better methodology in the estimation of this relationship. <\/p>\n\n\n\n Furthermore, a significant challenge faced by empirical works on Nigeria is the choice of proxy for economic crimes. Most of the empirical works reviewed used corruption perception index, which is subjective in nature with very short time points, as proxy for economic crimes and suggested that the direction of causality is from economic crimes to economic growth and not vice versa. Definitely, a variable that is largely objective in nature and has larger time points is preferable to the one that is subjective. <\/p>\n\n\n\n Therefore, this study aims at providing robust econometric analysis, which deepens the understanding of the relationship between economic crimes and economic growth in Nigeria both in the short run and long run within the uninterrupted democratic dispensation period of 1999 to 2013 using a state-space time-varying methodology. It is believed that this will shed brighter light on the impact of economic crimes on the Nigerian economy. The rest of the paper is structured as follows: section 1 is introduction while theoretical framework and empirical review are contained in section 2. Section 3 is the model specification and the analytical techniques while section 4 contains data presentation and analysis. Section 5 is conclusion.<\/p>\n\n\n\n Ezema et al (2012) posit that \u201ccorruption is endemic and has eaten deep into every facet of our national life. The productive and technological base is weak, outdated, narrow, inflexible and externally dependent. The infrastructure is poor, inadequate and lacks maintenance. The effectiveness of incentives has been generally low, giving rise to inadequate utilization of the factors of production. Furthermore, policy instability and summersaults are discouraging foreign investment despite the huge domestic market and the strategic location of the nation. The obvious effects have produced a weak private sector largely oriented towards distributive activities\u201d.<\/p>\n\n\n\n UNECA and UAC, 2012 observe that economic crimes affect indigenous entrepreneurship, more so with trade liberalization. Proceeds of economic crimes are used to bring in and \u2018dump\u2019 goods in the market, which are sold at prices below cost price in the exporting country. The reason for selling at a very low price is that economic criminals (money launderers) import so as to transfer their dirty money and not for profit motives. The situation depresses domestic production due to the uncompetitive pricing of the imported products. Because the return on investment on domestic production and other legitimate business activity will almost inevitably be lower than the high returns made by money launderers, domestic production is depressed by their activities. This situation affects small and medium scale enterprises which are the growth targets the government is addressing. Consequent to this development, foreign investment will decline, because investors will be scared of an economic environment where illicit monies are allowed to play a significant role in the allocation of resources. <\/p>\n\n\n\n Kar (2011) opines that money laundering impacts on the poorest in society potentially and most destructively too. It eviscerates foreign aid. It is argued that for every dollar, which is given to developing countries in aid, ten dollars flow back out in illegal funds. Half of the one trillion dollars of dirty money which flows across borders each year comes from developing countries.<\/p>\n\n\n\n The International Monetary Fund has registered inexplicable fluctuations in currency demand, prudential risks to bank soundness, contamination effects on legal transactions and heightened unpredictability of international capital flows and exchange rates due to money laundering (IMF, 2012). Osisioma (2009), states that in Nigeria, embezzlement of federal funds by certain state government actors has led, in many cases, to the naira\u2019s devaluation and concomitant sparse supply of sterling and US dollars as launderers purchase foreign currency to export. A more unstable financial environment precipitated by money laundering means a financial environment less conducive to sustained growth. The East Asian Financial Crisis of 1997, although an extreme case, was an example of how quick and unpredicted outflows of capital crippled several economies.<\/p>\n\n\n\n Classical Growth Theory<\/p>\n\n\n\n This theory sought to determine the sources and composition of growth and what can hinder growth. The proponents of this theory posit that the way income is distributed among classes in the society determines whether growth occurs or how growth proceeds. It also determines the saving behavior of classes in the society which is critical for growth. Therefore, growth flows from the distribution of income. High level of corruption distorts the allocation of public resources and leads to a more unequal distribution of income. Gupta, Davoodi, & Alonso-Terme (2002) in a study on corruption, inequality and poverty observed that high levels of economic crimes produce a more unequal distribution of income under some conditions, but the mechanism may be complex\u2014operating through lower investments in education and lower per capita incomes. Rotimi et al (2013) assert that there are strong indications that the changes in income distribution that have occurred in recent years in previously centrally planned economies have been partly the result of corrupt actions.<\/p>\n\n\n\n A continuous flow of production, income and expenditure is known as circular flow of income. The circular flow of income involves two basic principles: <\/p>\n\n\n\n 1). In any exchange process, the seller or producer receives the same amount what the buyer or consumer spends. <\/p>\n\n\n\n 2). Goods and services flow in one direction and money payment to get these flows in return direction, causes a circular flow.<\/p>\n\n\n\n In terms of the circular flow of income model, the leakage that financial institutions provide in the economy is the option for households to save their money. This is a leakage because the saved money cannot be spent in the economy and thus is an idle asset as not all output will be purchased. The injection that the financial sector provides into the economy is investment (I) into the business\/firms sector. The Economic theory posited by Keynes observed that all that is saved may not be invested, thus producing disequilibrium. Thus, banks sometimes are conduits for money laundering.<\/p>\n\n\n\n The Government Sector in the circular flow consists of the economic activities of local, state and federal governments. The leakage that the Government sector provides is through the collection of revenue through Taxes (T) that is provided by households and firms to the government. Economic crimes involving tax evasion and commercial mis–invoicing could shrink tax revenue. For this reason they are a leakage because it is a leakage out of the current income, thus reducing the expenditure on current goods and services. The injection provided by the government sector is government spending (G) that provides collective services and welfare payments to the community. When tax revenue shrinks due to economic crimes, government expenditure is affected.<\/p>\n\n\n\n The next sector in the circular flow of income model is the overseas sector which transforms the model from a closed economy to an open economy. The main leakage from this sector are imports (M), which represent spending by residents into the rest of the world. The main injection provided by this sector is the exports of goods and services which generate income for the exporters from overseas residents. Over-invoicing of export acts as a leakage instead of injection. Figure 3 below sheds more light on the flow.<\/p>\n\n\n\n The significance of the study of circular flow of income to this research can be seen in the measurement of national output\/income. National income is an estimation of aggregation of any of economic activity of the circular flow. It is either the income of all the factors of production or the expenditure of various sectors of the economy. However, aggregate amount of each of the activity is identical to each other. Again, the circular flow of income signifies the interdependence of each activity upon one another. For the economy to be in equilibrium, all the behaviours of all the components (both observed and unobserved) of the national income are important. Gupta et al (2002) in a study on corruption, inequality and poverty observed that high levels of economic crimes produce a more unequal distribution of income under some conditions, but the mechanism may be complex-operating through lower investments in education and lower per capita incomes. <\/p>\n\n\n\n In this sub-heading, the researcher explored previous empirical studies conducted in this area of study with a view to discovering the gap in literature, which formed the basis of this research. To this end, a number of works were reviewed both foreign and local.<\/p>\n\n\n\n Ekundayo et al., (2013), in a study to analyse Corruption and Economic Growth in Nigeria using GDP as the dependent variable and corruption, previous degrees of corruption and corruption perception index for Nigeria as explanatory variables and adopting OLS concluded that corruption impairs economic growth. This study failed to identify any scope or even identify the sources of data and so the reliability of data and result drawn there from are put in doubt. Moreover, corruption perception index is just the perception of individuals with regard to corruption and this perception is largely subjective with minimal time points.<\/p>\n\n\n\n Ahmad et al. (2012) using panel data from 1984 to 2009 for 71 developed and developing countries, with corruption index, corruption squared, bureaucratic efficiency index, political stability index, institutional efficiency index, risk to investment index etc while employing generalized methods of moments estimation (GMM) find that decrease in corruption raises economic growth rate in an inverted U-shaped way. <\/p>\n\n\n\n Aidt et al. (2008), in an empirical study on Governance Regimes, Corruption and Growth: Theory and Evidence in a panel data analysis using voice and accountability index, corruption index and gdp as variables found a non-linear relationship between corruption and growth and therefore concluded that there is no relationship between corruption and growth in countries with low-quality political institutions.<\/p>\n\n\n\n M\u00e9on and Sekkat (2005) in an empirical study on whether corruption greases or sands the wheels of growth using voice and accountability index, bureaucratic efficiency index, political stability index, institutional efficiency index as variables and employing panel technique conclude that corruption \u2018sands the wheel\u2019 of economic growth.<\/p>\n\n\n\n Lambsdorff (2003), using survey method in generating his data and employing descriptive statistics in his analysis, finds that corruption is responsible to reduced capital productivity among a panel of countries. This result reinforces the time allocation model of crime and economic growth. In this model, crime and work are substitutes. The more time is allocated to crime, the less time work gets and this implies lower human and capital productivity. Use of descriptive statistics only hampers robust analysis.<\/p>\n\n\n\n Cadernas (2007) focuses on relationship between growth rate and organized crime in an unbalanced panel of 65 countries and found that criminality in Columbia undermines economic growth through the productivity channel, after applying a growth accounting calculus. Indeed, the sources\u2013of\u2013growth decomposition shows that this reversal can be accounted entirely by changes in productivity induced by an increase in criminality.<\/p>\n\n\n\n Pinotti (2011) compares the post\u2013war economic growth of two different regions (treated group) in southern Italy exposed to the presence of mafia organizations after the 1970\u2019s with a hypothetic control group, using synthetic control methods. The comparison of actual and counterfactual development shows that the presence of mafia mitigates regional GDP per capita by 16 per cent, at the same time as murders increase sharply for the synthetic control group.<\/p>\n\n\n\n Gaibulloev and Sandler (2008) measured the impact of domestic and transnational terrorism on income per capita growth for 1971-2004 in a panel of 18 Western European countries and concluded that there is a negative but significant relationship between crime variables (economic costs of domestic and transnational crimes) and income per capita growth.<\/p>\n\n\n\n Gupta (2004) analyzes the consequences of conflict index on economic growth within a three\u2013equation cross section structural model for a panel of countries. He finds that conflict index has no direct effect on economic growth, but has an indirect effect by increasing defense spending share, which lowers economic growth.<\/p>\n\n\n\n Peri (2004), using a large data set from 1951 to 1991, shows that annual per capita income growth in Italy is negatively affected by murder. <\/p>\n\n\n\n Narayan and Smyth (2004) used the Granger Causality Test within an Auto Regressive Distributed Lag (ARDL) Model to determine the relationship between different crime typologies (arms trafficking and human trafficking) on the one hand and real wage rate and unemployment in Australia, on the other. The study finds that proliferation of arms and human trafficking deteriorated unemployment and wage rate. The study links increase in participation in crime to proliferation of arms, which breeds unemployment as the number of prison sentences increases. This study aligns with the Time Allocation Model. <\/p>\n\n\n\n Mauro et al (2007) test the link between unemployment, economic growth and human trafficking using Italian regional data. Employing Ordinary Least Square technique, the study found that human trafficking impacted negatively on the GDP of the economy as well as increase unemployment rate. The influx of illegal immigrants into Italy for prostitution and pornography put a downward pressure on existing facilities and thus cause increase in government spending on infrastructure and other social services.<\/p>\n\n\n\n Chen (2009) examines the long-run and causal relationships among cyber crime, unemployment and income for Taiwan, using a Bounce Test Approach. The study finds significant negative relationship between cyber crime, income and unemployment in Taiwan with a unidirectional effect of crime on economic variables.<\/p>\n\n\n\n Detotto and Pulina (2009) applied an ARDL Model from 1970 to 2004 for Italy to assess the relationship between deterrence indicators, multiple crime offences and economic performance. They conclude that cyber crime affected the GNP of the economy negatively while deterrence indicators did not substantially reduce the number of cyber crimes committed within the period.  <\/p>\n\n\n\n Baharom and Habibullah (2009) examined the relationship between real gross national product (GNP) and cyber crime. Applying an ARDL model for Malaysia, the study shows that cyber crime has negative but significant impact on the GNP of the country. They, therefore, advocated for strong and water-tight security code for banks and stiffer penalty for those found culpable.<\/p>\n\n\n\n Detotto and Otranto (2010) presented an empirical analysis of macroeconomic consequences of criminal activity (murder) in Italy from 1979 to 2002. Dealing with an AR model incarnated in a state space model, a time\u2013varying parameter approach was employed to measure the short-run impact of criminality on real GDP. Results show that murder has a strong permanent component which has a significant negative impact on economic performance.<\/p>\n\n\n\n Adewale (2011) discovered a strong significant negative relationship between economic crime and output growth in Nigeria. He undertook an empirical investigation of the relationship between a number of key variables in Nigeria. After carrying out a test of stationary and co integration properties on the variables, he further estimated the econometric parameters of the variables which included Gross Domestic Product (GDP) as the dependent variable and Gross Capital Formation (GCF), Money Supply (MS), Public Domestic Investment (PINV), Corruption Perception Index (CPI), bank fraud, External Debt (EXTD) and Unemployment Rate (UNEMPL) as the explanatory variables, and concluded that economic crime has a crowding-out effect on growth within the period of 1996 to 2009. The time points are small to allow for generalizations of this nature. Again, the use of corruption perception index as a proxy for economic crime may hide other characteristics of economic crime and so hamper robust econometric analysis.<\/p>\n\n\n\n Fabayo, Posu & Obisanya (2011), in their study analyzed the consequences of economic crime on investment in Nigeria using the Ordinary Least Square technique. They used the annual corruption perception index between the period 1996 and 2010 as proxy for economic crimes. Their study revealed that low Corruption Perception Index ranking on Nigeria, which implies high level of corruption, leads to low investment and thus low economic growth in Nigeria. The time points are small to allow for generalizations of this nature. Again, the use of corruption perception index as a proxy for economic crime may hide other characteristics of economic crime and so hamper robust econometric analysis.<\/p>\n\n\n\n In another related study which focuses on the relationship between economic crime and development, Akindele (2005) undertook an empirical investigation of the relationship between a number of key variables in Nigeria. Estimating a modified production function that includes labour, capital and political instability, corruption index as variables found that there exists a strong significant negative relationship between economic crime and development. The time points considered here are too short for such conclusions to be drawn. The use of OLS linear regression without investigating the nature of the relationship between economic crimes and economic growth will definitely yield misleading result.<\/p>\n\n\n\n Nageri et al. (2013) while adopting Ordinary Least Square (OLS) linear technique tested the hypothesis that corruption perception index affects economic development (GDP) and found the result to be statistically significant, meaning that Corruption Perception Index (CPI), a proxy for economic crime in this research negatively affects economic development. On the other hand, the null hypotheses of Corruption Rank (CR) and Relative Corruption Ranking (RCR) of Nigeria among countries under review were not accepted meaning that the relative position of Nigeria among countries under review and Nigeria\u2019s rank on corruption cadre is also statistically significant. The proxy for economic crime is a subjective variable and may not be an adequate measure of economic crime since they depend largely on the perceptions of people. <\/p>\n\n\n\n Different models can be used to estimate the relationship between economic crimes and economic growth. Ahmad et al (2012) adopted the standard production function, which extends Solow\u2019s original approach to growth accounting process while Detotto et al (2010) adopted OLS technique incarnated in a State Space Model enabling the capture of time-varying elasticity coefficient of crime on growth. The point of divergence of the present study from that used by Detotto et al (2010) is that the present study used economic crimes (Illicit Financial Outflows as proxy) instead of murder as one of the explanatory variables explaining economic growth.<\/p>\n\n\n\n Detotto et al (2010) observed that a quick way of determining the nature of the relationship between two variables is to plot their scatter diagram. Figure 4 plots the scatter diagram of Illicit Financial Outflows and RGDP for Nigeria over 1970 through 2013.<\/p>\n\n\n\n HOW TO RECEIVE PROJECT MATERIAL(S)<\/strong><\/p>\n\n\n\n After paying the appropriate amount (#5,000) into our bank Account below, send the following information to<\/strong><\/p>\n\n\n\n 08068231953 or 08168759420<\/strong><\/p>\n\n\n\n (1)    Your project topics<\/p>\n\n\n\n (2)     Email Address<\/p>\n\n\n\n (3)     Payment Name<\/p>\n\n\n\n (4)    Teller Number<\/p>\n\n\n\n We will send your material(s) after we receive bank alert<\/p>\n\n\n\n BANK ACCOUNTS<\/strong><\/p>\n\n\n\n Account Name: AMUTAH DANIEL CHUKWUDI<\/p>\n\n\n\n Account Number: 0046579864<\/p>\n\n\n\n Bank: GTBank.<\/p>\n\n\n\n OR<\/p>\n\n\n\n Account Name: AMUTAH DANIEL CHUKWUDI<\/p>\n\n\n\n Account Number: 3139283609<\/p>\n\n\n\n Bank: FIRST BANK<\/p>\n\n\n\n FOR MORE INFORMATION, CALL:<\/strong><\/p>\n\n\n\n 08068231953 or 08168759420<\/strong><\/p>\n\n\n\n AFFILIATE LINKS:<\/a><\/p>\n\n\n\n myeasyproject.com.ng<\/a><\/p>\n\n\n\n easyprojectmaterials.com<\/a><\/p>\n\n\n\n easyprojectmaterials.net.ng<\/a><\/p>\n\n\n\n easyprojectsmaterials.net.ng<\/a><\/p>\n\n\n\n easyprojectsmaterial.net.ng<\/a><\/p>\n\n\n\n easyprojectmaterial.net.ng<\/a><\/p>\n\n\n\n projectmaterials.com.ng<\/a><\/p>\n\n\n\n googleprojectsng.blogspot.com<\/a><\/p>\n\n\n\n myprojectsng.blogspot.com.ng<\/a><\/p>\n\n\n\n \nhttps:\/\/projectmaterialsng.blogspot.com.ng\/\n<\/div><\/figure>\n\n\n\n \nhttps:\/\/foreasyprojectmaterials.blogspot.com.ng\/\n<\/div><\/figure>\n\n\n\n \nhttps:\/\/mypostumes.blogspot.com.ng\/\n<\/div><\/figure>\n\n\n\n \nhttps:\/\/myeasymaterials.blogspot.com.ng\/\n<\/div><\/figure>\n\n\n\n \nhttps:\/\/eazyprojectsmaterial.blogspot.com.ng\/\n<\/div><\/figure>\n\n\n\n \nhttps:\/\/easzprojectmaterial.blogspot.com.ng\/\n<\/div><\/figure>\n\n\n\n \n\n\n\n [1]<\/a> Ibid. Pp.229<\/p>\n\n\n\n [2]<\/a> Ibid. Pp.229<\/p>\n","protected":false},"excerpt":{"rendered":" ATTENTION: BEFORE YOU READ THE ABSTRACT OR CHAPTER ONE OF THE PROJECT TOPIC BELOW, PLEASE READ THE INFORMATION BELOW.THANK YOU! INFORMATION: YOU CAN GET THE COMPLETE PROJECT OF THE TOPIC BELOW. THE FULL PROJECT COSTS N5,000 ONLY. 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