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A STUDY ON PARLIAMENTARY V/S PRESIDENCTIAL SYSTEM OF GOVERNMENT

This research paper is a comparison between the system of parliamentary government and a presidential form of government. It tries to highlight the features and their benefits of having both the governments and tries to enunciate a historical debate with a discussion about the adoption of parliamentary form of government in Indian political scene and emphasize the factors that drove India to adopt the Parliamentary system of government in the long run.

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PARLIAMENTARY SYSTEM(S) or/and PRESIDENTIAL SYSTEM(S): DILEMMAS AND CHALLENGES

Gordana Siljanovska- Davkova

The author analyzes the contemporary models of government, including the Macedonian one, through the relations between legislative and executive, at normative level and in practice. According to her, the problematic and relative methodological value of the dichotomy “parliamentarism-presidentialism” in classification of government can be also seen in the Macedonian example of “separation” of powers. The Macedonian “constitutional cocktail” is even more complicated and more hybrid in the practical functioning of institutions due to absence of democratic tradition and civic political culture, due to partytocratic state, strong elements of ethocracy as well as due to fragile civil society. Key words: separation of powers, government, parliamentarism, presidentialism, semi-presidentialism, democracy, consociational model of democracy, partitocrazia

Santhanam Prabhakar

Facta Universitatis, Series: Law and Politics

geetika sood

Academia Letters

Roopali Shekhawat

Yağmur Akar

Journal of International Relations and Political Science Studies

Ramachandra Byrappa

Indian democracy has come of age, and it is probably time to abandon the colonial heritage as far as its parliamentary system is concerned. Transactionality is the name of the game in India’s parliamentary system, where the principle of representation is fast fading. The art of coherent electoral manifestos and democratic debate on the policy promises it contains is a distant reality. The democratic debate and electioneering are replaced by vote banks, MPs crossing the floor, personality cult and other deification of political leaders through social media hammering. The end result is the loss of morality among parliamentarians, transforming the legislature into a financial clearing house. The situation is further worsened by two other problems related to the parliamentary process in India. The first among these two problems is political consensus. National development, economic and social needs, demand a broad consensus and popular affirmation on a few central policies and issues to move this gigantic country forward through the next few decades that are going to be very difficult. The only Indian statesperson that could build such a consensus was Indira Gandhi. Today India is divided and confused with no clarity of purpose, dogmatic leadership cannot replace charismatic statesmanship. One can therefore legitimately ask a very simple question: Is it time to make a leap towards a Presidential system, where the President is directly elected through universal suffrage? Could this help to give India one national figure, one clean voice and one articulation of the National Interest? The main argument of this essay is that colonial heritage is causing institutional blockage and dysfunctionality in the Indian political set-up. The methodology used is a structural and historic analysis of the Indian parliamentary system.

Parliamentary and Presidential Democracies: Which One is Best? With the exception of the United States, where a system of separation of executive and legislative powers exists, all countries that are considered to be stable democracies adopt a constitution that is, at least partially, parliamentary. A parliamentary constitution is characterized by the fusion of executive and legislative powers, achieved by the fact that the government needs the confidence of a majority in the legislative assembly in order to come to and remain in power. Parliamentarism is popular among both academics and politicians. The main reasons for this follow from the crucial distinction between parliamentarism and presidentialism: the fact that under parliamentarism legislatures may remove the government via the approval of a vote of no-confidence. When such votes are passed, either a new government is formed or, in case this is not possible, new elections are held. Under presidentialism, in turn, the government and the legislature serve fixed and independent terms in office. T This basic difference is thought to produce a number of consequences for the way these systems operate: • • • • Under presidentialism, it is thought, governments are not likely to be supported by a majority of the legislature since there is nothing in the system that guarantees that such a majority will exist. Deadlocks between the government and the legislature, thus, would be common under presidentialism and would lead to conflict between the two powers. Coalitions in presidential regimes are thought to be rare, again due to the fact that noting in the system would provide the incentives for individual politicians and their political parties to cooperate with one another and the government. Decision-making under presidentialism is normally considered to be decentralized, that is, to be such that the president simply responds to proposals originated in the legislature, which is, in turn, organized in such a way as to allow for politicians to pursue individualistic rather than partisan strategies. As a consequence, the government's ability to influence and implement policy is reduced and " crises of governability " are more likely to occur. Together, thus, these observations may seem to make a compelling case that countries seeking to establish a lasting democratic order should adopt a parliamentary form of government. Yet, none of these arguments is sufficient to make a presidential regime an unattractive choice per se. To begin with, democracies at low levels of income per capita face high risks of collapse, regardless of their form of government. As a matter of fact, when per capita income is less than $1,000 (in 1985 PPP USD), parliamentary democracies are more likely to die (that is, to become a dictatorship) than presidential democracies: the expected life of the former is 7 years whereas the expected life of the latter is 10 years. The difference is not very large and hence not much should be made of it. What matters is that, at low levels of income, both types of democracy face equally high risks, with the form of government making little difference for the survival prospects

Dr. Mahboob Hussain

sohail amjad

India is one of the oldest civilizations and one of the largest countries of the world both in terms of territory and population. After going through several phases of wars and colonization by foreign invaders like the Mughals and the European powers for centuries, India was able to make its democracy only after independence in 1947 which was considered to be the largest democracy by electorate under the leadership of its nationalist movement The Indian National Congress. Since its creation in 1947 India has proved and sustained itself as one of the strongest and successful democratic state in the world. It has become a role model for many countries of the third world. Its a fact that even the developed countries of the world are much interested and surprised with the sustainability of the Indian democratic system. The essay is about the indian political system, its emergence, its infrastructure, the frame and strategies for managing the greatest democratic system. I have also mention the system of political parties their fall and rise and the emergence of new parties and the merging or renaming of certain political parties. I have also thrown light on the ups and downs of the voting percentage, their reasons behind and their maintenance of vote bank. i have made a closer look at five trends that have unfolded over the last six decades illustrates why the election will likely hinge on a confluence of local factors. The most striking trend in Indian electoral politics is the explosion in political competition in recent years. In the 1952 general election , the first held after India won Independence, 55 parties took part; in 2009, 370 parties entered the fray. The surge in political competition began in the 1980s -the number of parties contesting elections jumped from 38 in 1984 to 117 in 1989, a watershed year in Indian politics. It was only the second time since Independence that the Congress Party was ousted from power. The dramatic surge in 1989 is explained by the proliferation of regional parties, which formed in direct response to popular disenchantment with Congress rule and the lack of representation for lower and backward castes, minorities, and regional or sub regional interests. With the 1989 election there was end to the single party rule and brought into practice the new governments formed under multi party coalition. This further gave way to many regional parties whose leader found that they can bring about considerable influence in the government making with even a small number of seats in the parliament. However putting light on such incidents in the party mechanism of india i will throw light on the current status of the indian political system ,the ups and downs in the government formation by differnet political parties . however my focus will be on the elections held in the past two decades and the volatilities and the factors of volatilities in the different election faced by several political parties.

Indian Parliament's evolution since 1947 and the case study of the 15th Lok Sabha (Parliament of India) showcases how the parliamentary democracy has evolved under different periods of time and how coalition governments have contributed in their own way to make parliamentary democracy a vibrant entity.

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Digital governance: government strategies that impact public services

• Review Article
• Published: 15 November 2022
• Volume 2 , pages 427–452, ( 2022 )

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• Francis M. Idzi 1 &
• Ricardo Corrêa Gomes   ORCID: orcid.org/0000-0002-4164-5986 2  

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The purpose of this study is to carry out a systematic literature review with meta-analysis, seeking to understand, from the perspective of public governance, how the Digital Era of Governance is impacting governments, which social contracts should be considered in a digital governance model, and which are the main barriers of digital government to the public policies design. The research uses the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol to record the evidence found. The contribution of this study to the observation of Digital Era Governance for government strategies points out that the most evident component of reintegration in governments are government portals that promote detachment from the central government and reduction of the burden on the State, the most apparent holism component are the digital services of social benefits, and the most evident digitization component were government portals with full availability of State services and improved search. Evidence is shown that government as a platform is the social contract model most available to society. It is also pointed out that the lack of knowledge and experience in technology was the most significant barrier to designing public policies focused on digital government.

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Research Article

The impact of the government response on pandemic control in the long run—A dynamic empirical analysis based on COVID-19

Contributed equally to this work with: Yuxun Zhou

Roles Data curation, Investigation, Methodology, Software, Writing – original draft

* E-mail: [email protected]

Affiliation School of Business, University of Southern Queensland, Toowoomba, Queensland, Australia

Roles Supervision, Writing – review & editing

¶ ‡ MMR and RK also contributed equally to this work.

• Yuxun Zhou, 
• Mohammad Mafizur Rahman, 
• Rasheda Khanam

• Published: May 4, 2022
• https://doi.org/10.1371/journal.pone.0267232
• Reader Comments

Although the outbreak of the Corona Virus Disease 2019 (COVID-19) occurred on a global scale, governments from different countries adopted different policies and achieved different anti-epidemic effects. The purpose of this study is to investigate whether and how the government response affected the transmission scale of COVID-19 on the dynamic perspective.

Methodology

This paper uses a dynamic generalized moment method to research the relationship between the government response and COVID-19 case fatality rate by using panel data from eight countries: China, United States, Canada, Australia, Italy, France, Japan, and South Korea.

We have the following findings: 1. Government responses have a significant impact on the scale of COVID-19 transmission. 2. The rate of increase of government responses on the growth rate of COVID-19 case fatality rate has the characteristics of cyclicity and repeatability, that is, with the increase in the growth rate of government responses, the COVID-19 case fatality rate shows the following cyclical motion law: increasing first, reaching the maximum point, and then declining, and finally reaching the minimum point and then rising; ultimately, its convergence becomes 0. The cyclical fluctuations of COVID-19 in the long term may be caused by the decline in the level of government response, the mutation of the virus, and the violation of restrictive policies by some citizens. 3. The government response has a lag in controlling the spread of COVID-19.

Originality/Value

Since there is a lack of literature on the impact of government responses on the development of COVID-19 from a long-term and dynamic perspective. This paper fills this gap in empirical research. We provide and expand new empirical evidence based on the current literature. This paper provides the basis for government decision-making and will help to formulate the response to other major public health events that may occur in the future.

Citation: Zhou Y, Rahman MM, Khanam R (2022) The impact of the government response on pandemic control in the long run—A dynamic empirical analysis based on COVID-19. PLoS ONE 17(5): e0267232. https://doi.org/10.1371/journal.pone.0267232

Editor: Siew Ann Cheong, Nanyang Technological University, SINGAPORE

Received: November 3, 2021; Accepted: April 5, 2022; Published: May 4, 2022

Copyright: © 2022 Zhou et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The data underlying the results presented in the study are available from https://github.com/OxCGRT/USA-covid-policy .

Funding: The author(s) received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

1. Introduction

In early 2020, COVID-19, which originated in China, gradually but inexorably spread around the world. What had started as an epidemic evolved into a pandemic. COVID-19 is very easily transmitted, mainly through close contact with others, and particularly through airborne transmission [ 1 ], with a relatively high infection and mortality rate [ 2 ]. Governments around the world have adopted different degrees and types of response policies to control the spread of COVID-19. Different response policies in different countries correspond to different control effects. Countries such as Japan [ 3 ], South Korea [ 4 ], China [ 5 ], and Australia [ 6 ] have achieved the desired results through strict control policies. European countries ( https://www.ecdc.europa.eu/en ), some other Asian countries and South American countries originally achieved some level of control through stringent policies, but once they were relaxed, new outbreaks occurred.

Government response is the most important component of disaster management. [ 7 ] summarized disaster management in four parts: mitigation, preparedness, response, and recovery. " The response phase of disaster relief happens right after a disaster occurs and refers to any activities that work to take care of the damage caused by the disaster " [ 7 ]. Research on government response and disaster management involves seven aspects: 1. How to achieve the optimal allocation of resources [ 8 ]; 2. Project schedule [ 9 , 10 ]; 3. The interaction between the government and the company [ 11 ]; 4. The evacuation process [ 12 ]; 5. The decision-making system [ 13 ]; 6. Network analysis [ 14 – 16 ]; 7. Supply chain optimization [ 17 ]. Therefore, the impact of response on disaster management is multidimensional. COVID-19 has also been a disaster for humans. Therefore, it is important to study the impact of the government response on the scale of the pandemic to reduce the losses caused by COVID-19. Unlike some public health emergencies in the past, COVID-19 is characterized by long duration and rapid spread. COVID-19 continues to appear around the world today. In contrast to the SARS virus, COVID-19 has not disappeared because of rising temperatures. Therefore, it has been postulated that humans will continue to struggle with COVID-19 for a long time. Consequently, based on the above background statement, it is important to investigate the relationship between government response and COVID-19 control over the long term. In the case of COVID, which continues to mutate, this is a dynamic relationship and is therefore more difficult to control.

There is a lack of literature on the impact of government response on the development of COVID-19 in the long-term from a dynamic perspective. To the best of our knowledge, no such studies are found in the existing literature. This is the main motivation for pursuing this research.

Against this backdrop, we propose the core research topic in this paper: the impact of the government response on pandemic control in the long run. We put forward the following two research questions:

• Q1 : Can the government response affect the spread of COVID-19 in the long run?
• Q2 : How has the government response affected the spread of COVID-19 in the long run?

The main contributions of this research are follows: First, we fill in the empirical evidence for dynamic pandemic research. We examine the dynamic process of government responses to the development of COVID-19. Based on the dynamic trajectory of COVID-19, we provide relevant policy recommendations. 2. Our findings will provide empirical evidence for management of the COVID-19 outbreak and help governments make appropriate decisions.

In the second section, we will briefly review the literature on COVID-19 and government response research. In the third section, we introduce an economic model and econometric methods. In the fourth section, we make an empirical analysis. In the final section, we conclude the paper with policy implications.

2. Literature review

There is a lack of relevant economic literature on COVID-19, as it is a new theme for research. We have searched extensively for literature on the issue of COVID-19 and government responses but failed to locate any research outputs on this topic. In this paper, we intend to fill this gap.

Existing literature on COVID-19 and government responses are all based on the Stringency Index of the University of Oxford. [ 18 ] used the index to study the driving factors of citizens’ satisfaction with government responses. They found that citizens are more concerned about the results of COVID-19 control than the policies the government had adopted. They also found that citizens’ satisfaction with the government’s response varies greatly from country to country. In conclusion, they analyzed a possible controversy: governments, in implementing possible exit strategies to escape the current lockdown, generally try to strike the right balance between the impact on public health (saving lives) and the impact on the economy (saving jobs). Some governments would prefer to reopen their markets to minimize the impact of the outbreak on their economies, while others are reluctant to take this course of action because it could lead to a rapid increase in infections. This is also one of the problems addressed by this paper. We will provide empirical evidence for this argument.

Delays in policy can lead to serious consequences. [ 19 ] studied the impact of policy decisions on mortality. They found that policy delays increased mortality (travel restriction policies, public advocacy policies, etc.). They believed that testing policies may also have an impact on mortality rates. An increase in the number of tests might reduce the death rate.

[ 20 ] studied the impact of restriction policies on COVID-19 in East Asia. They found that the incidence of COVID-19 decreased after the implementation of a non-pharmacological intervention. They judged that citizens’ responsibility, collectivism, and vigilance were the three main reasons for the success of COVID-19 in East Asia. They undertook a short-term analysis of the impact of the government response on COVID-19. However, the battle against COVID-19 is long- term. In the long run, whether the government response (restriction policy) is effective for epidemic control remains a gap in the literature. This is also one of the main problems analyzed in this paper.

Other studies have explained the informational impact of the government response on epidemic control. Before COVID 19 appeared, [ 21 ] had studied how a government should respond to a pandemic. They considered that the best response would be transparency and accountability. [ 22 ] researched the Philippine government’s response to the COVID-19 outbreak in the Philippines, demonstrating that transparency and good information delivery mechanisms are key to dealing with public events.

Combining the above research literatures on COVID-19 with the government response, we find that there is a lack of dynamic research on the long-term effects between the government response and COVID-19. Whether and how the government response will affect the development of the pandemic in the long term is a research gap in the existing literature.

3. Methodology

3.1 theoretical model.

Since panel data contains more information and can minimize estimation bias [ 24 ], we chose panel data analysis based on eight countries: China, the United States, Canada, Australia, France, Italy, Japan, and South Korea. These countries are selected because they have been greatly affected by COVID-19 and/or have complete relevant data. Other countries that are heavily affected by COVID-19, such as the United Kingdom, Brazil, and India, have not been included in this paper due to incomplete statistical data. Our aggregate sample data are monthly.

In fact, we face the problem of insufficient control variables due to lack of data. According to the conclusion of the economic model above, our control variables should have included age, gender, outdoor consumption per month, indoor consumption per month, total number of hospitals per month, ICU beds per month, average education level of medical staff, and happiness index of citizens. Therefore, for those variables that lack of data, we can only substitute other variables for observations. We use a country’s economic growth rate to indirectly observe a country’s health environment, including total number of hospitals per month, ICU beds per month, average education level of medical staff. We can indirectly observe the health environment of a country through its economic growth rate. It is true that the health environment observed through economic growth rates is not very accurate. However, since we use the monthly data from 2020, which is micro data, the statistical imperfections of the healthcare environment in various countries leads us to use other control variables to replace the original control variables. We reviewed many databases online, and we originally intended to replace the growth rate of the economy with better health care expenditure as a control variable for the health care environment. However, we found that countries’ health expenditure was only counted up to 2018 or 2019. For the above reasons, we chose the economic growth rate as a surrogate variable for the medical environment. The better a country’s economic development, the better its infrastructure and the more it invests in people’s livelihoods. We will further explain the econometric variables in section 4.

The original sample data of the dependent variable (the number of confirmed cases) and the independent variable (the government response) are collected from the Stringency Index for Government Response during COVID-19 (from 2020-01-01 to 2021-02-30) of the University of Oxford [ 25 ], which are collected in the form of daily statistics (Source: https://ourworldindata.org/grapher/covid-stringency-index ). [ 25 ] launched the Oxford COVID-19 Government Response Tracking System (OxCGRT), which provides a systematic way to track national and local jurisdictions’ response to COVID-19 over time. They combined the data into a series of novel indices that combined various government responses. These indices are used to describe changes in these responses, explore whether they affect infection rates, and determine correlations between different degrees of response. Our raw data of control variables (GDP growth rate and inflation rate) and instrument variable (Government Budget) have been collected from the Take-Profit Organization website (Source: https://take-profit.org/en/ ). We used the quadratic interpolation to convert frequency for these data from daily to monthly.

3.3 Econometric approach

Our data belong to large “ T ” (Time) and small “ N ” (Cross-section). Thus, we need to carry out a unit root test, co-integration test and causality test on the time series of variables to ensure their stationarity, their long-term equilibrium relationship and their statistical causality. The following unit root tests will be used to underpin our paper: [ 26 – 28 ], augmented Dickey–Fuller (ADF) and Phillips-Perron (PP). We will use the covariance test of [ 29 ] and [ 30 ] to test whether there is a long-term equilibrium relationship between our variables.

[ 30 ] uses the same basic method as the Pedroni test. However, the biggest difference between them is that in the first stage of the Kao test, the regression equation is set as each cross-section individual has different intercept terms and the same coefficient, and all trend coefficients are set as 0.

Where υ it = α i + u it .

If the value of the calculated statistic F 1 is not less than the corresponding critical value under the given confidence, then the hypothesis H 1 needs to be rejected and we choose the varying-coefficient model. Instead, we choose the Intercept change model.

We get 46.3763, 75.9119, and 75.5645 for S 1 , S 2 , and S 3 , respectively. N = 8, k = 4 and T = 11. Thus, F 2 = 0.8632< F [35,48]. Therefore, we choose the constant coefficient model. In order to eliminate the heteroscedasticity of residuals and sequence autocorrelation, the cross-section SUR weighted method is used to estimate the parameters in OLS and TSLS. Cross-section SUR weighting is also used to estimate the covariance of the coefficients.

4. Empirical analysis and implications

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https://doi.org/10.1371/journal.pone.0267232.t001

Table 2 shows the mean standard deviations of the sample population and each section. Overall, the average case fatality rate is stable at 3%, up from the previous period. Governments responded by average growth at 0.6%, showing that the pandemic control around the world had some success. In terms of individual cross-section, Japan has the lowest average (−0.01) and China has the lowest standard deviation (0.00) of the case fatality rate, indicating that the pandemic is effectively controlled (with lower outbreak risk) in China. The highest average growth rate of case fatality rate is in Canada. Standard deviation in France is the highest, showing that the pandemic is not well controlled in France. From the independent variable GOV _ R , the average growth rate of government response is the lowest in China and Australia, and both of their standard deviations are small. The lowest standard deviation and mean denote that the anti-pandemic response of China has entered a convergence state. During COVID-19, the country with the highest average GDP growth rate was Canada while the high standard deviation indicates that Canada’s GDP growth was not stable. Average GDP growth in most countries is negative, which may indirectly indicate the impact of COVID-19 on economic growth.

https://doi.org/10.1371/journal.pone.0267232.t002

4.1 Panel unit root test

As stated before, in order to make the time series stable, we do the stationarity test for the time series of various variables. We use four unit root tests: the [ 26 ] test, [ 27 ] test, [ 28 ] test, augmented Dickey–Fuller (ADF) test and Phillips-Perron (PP) test. Table 1 in S1 Appendix presents the level and first order difference test results of unit roots of each variable under four different methods. Table 3 shows that all variables are single integer at levels, that is I (0).

https://doi.org/10.1371/journal.pone.0267232.t003

4.2 Panel co-integration test

Using the co-integration test method of [ 29 ] and [ 30 ], we conduct the co-integration test for the long-term relationship between variables. Kao test results show that the test passed the co-integration test. Pedroni test results show that half of the statistics pass the co-integration test. After comprehensive analysis, we believe that there is a long-term equilibrium relationship between the variables.

4.3 Regression results

Table 4 shows the regression results under four regression methods. Empirically, there is a two-way causality between the growth rate of government response and the case fatality rate, that is, an increase (decrease) in the growth rate of government response will lead to a decrease (increase) in the case fatality rate. Thus, two-way causality creates possible endogenous problems. To solve the endogenous problem, we used TSLS and a dynamic GMM method to re-estimate the parameters. The results show that the parameters estimated by TSLS and dynamic GMM method are basically consistent with the parameters estimated by the OLS method, which verifies the effectiveness of our parameter estimation.

https://doi.org/10.1371/journal.pone.0267232.t004

We choose government budget ( GOV _ E ) and economic support ( ECO _ S ) during COVID-19 as instrumental variables. The selection of instrumental variables needs to be highly correlated with endogenous independent variables and independent of random disturbance. The main government response is from the government budget. Economic support during the pandemic is also the most effective way to control the pandemic. Therefore, both government budget and economic support are intermediate variables, which are highly correlated with independent variables and independent of the disturbance term.

It is not difficult to find that our independent variable is significant at the 1% and 5% confidence level. Under OLS, TSLS and dynamic GMM methods, D . W .∈[1.59,2.31] (In the TSLS, the initial D . W . is 0.9198, indicating that the model has positive first-order autocorrelation. Therefore, after we added AR (1), D . W . becomes 1.867, indicating that there is no first-order sequence autocorrelation in the model) proves there is no first order sequence auto-correlation. The P value of the Hansen J statistic shows that the null hypothesis of [ 34 ] test cannot be rejected. Therefore, the moment condition of over-recognition is valid, that is, the instrumental variables selected by our model are valid. The first-order statistics of the Arellano-Bond test for the differential GMM model are significant under the 10% level. The second-order statistics are not significant, which indicates that the model does not have second-order sequence auto-correlation. It shows that our model has been set up correctly.

The estimation results of the four methods show that the parameters α 1 , and β are significantly positive. The results show that the outbreak of COVID-19 has inertia characteristics. The case fatality rate of the previous period will significantly affect the case fatality rate of the current period. It means that if the government had not taken timely measures to control the COVID-19 outbreak in the previous period, then the government would need to take more measures for the current period to control COVID-19. There is a cyclical relationship between the growth rate of government response and the case fatality rate of COVID-19 (see Fig 1 ).

https://doi.org/10.1371/journal.pone.0267232.g001

Our regression results are consistent with those presented by the statistical description. The government response has been the most effective way of controlling the scale of the COVID-19 outbreak. China first used strict restrictive policies to control the development of COVID-19 in China, and finally succeeded in controlling the development of the pandemic [ 35 ]. Since then, China has resumed production and daily activities, and the economy has gradually begun to recover [ 36 ]. This is in line with our suggestion: in the stage of rising pandemic scale, the government should aim to control the pandemic and improve economic development; in the declining stage of the pandemic development, the government should take economic development as the goal and make the government response. Australia is one of the most successful countries in controlling COVID-19. The Australian government adopted a rigorous government response in the early stages of the outbreak and achieved effective results [ 6 ]. The positive impact of an active government response in controlling the development of COVID-19 is well illustrated by the cases of China and Australia. Strict restrictions are the most important part of the government’s response. Strict restrictions, including social distance restrictions, mandatory mask wearing, travel bans, etc., are positive government responses. According to our findings, if the government maintains a positive response, based on the cyclical relationship between the government response and the COVID-19 fatality rate, the government will have fewer costs and be able to contain the epidemic for some time. Japan and South Korea also adopted relatively strict government response policies after COVID-19 occurred and achieved the expected results [ 37 ].

4.4 Discussion and implication

Some actual evidence supports our regression results that the growth rate of the government response has a cyclical effect on the case fatality rate. The first case of community transmission in Canada was confirmed on 5 March 2020. The Canadian government immediately declared a state of emergency [ 38 ]. Canadian provinces and territories have, to varying degrees, implemented closures of schools and day care facilities, bans on gatherings, closures of non-essential businesses and restrictions on access. The Canadian government at that time required all travellers returning to the country to self-quarantine for 14 days. After that, active cases in Canada continued to decline until late summer and early winter. In September 2020, cases rebounded in all Canadian provinces and territories [ 39 ]. On 23 September 2020, the Canadian government announced that Canada was experiencing a second wave of the epidemic [ 40 ]. As cases have increased, the government has again imposed new restrictions, including lockdowns in different areas. In December 2020 and January 2021, cases, hospitalizations, and deaths in Canada spiked around the Christmas and holiday seasons. Therefore, the Canadian government imposed strict restrictions (such as lockdowns and curfews) again across the country. These closures led to a steady decline in active cases [ 41 ]. Following the third and fourth wave, which occurred between March and October 2021, the Canadian local government reinstated the travel ban. At the time of the fourth wave, it was also referred to as an "unvaccinated pandemic" because of Canada’s high vaccination rates. Similarly, Canadian provincial and territorial governments have reimposed restrictions around travel and quarantine.

France has already experienced three waves of the virus. On 12 March 2020, in the first wave of the outbreak, the French government announced the closure of all schools and universities, a ban on gatherings of more than 100 people, excluding public transport, and the closure of all non-essential public places including restaurants, cafes, cinemas and nightclubs [ 42 ]. Since then, the French government gradually lifted the blockade [ 43 ]. From August 2020, the rate of infection increased, with France recording 26,896 new infections in Europe in a 24-hour period on 10 October 2020. This increase led France to enter a second nationwide lockdown on 28 October 2020. The French government announced its third nationwide lockdown from April 3, 2021. The restrictions included the closure of non-essential stores, the suspension of schools, a ban on domestic travel and a nationwide curfew from 7pm to 6am.

Italy experienced the first wave of the epidemic from February 2020. The government suspended all flights and declared a state of emergency. The Italian government closed all non-core businesses and industries and restricted the movement of citizens [ 44 ]. Restrictive measures had had an initial positive effect [ 45 ]. By May 2020, many restrictions were gradually eased and freedom of movement between Italian regions and other European countries was restored [ 46 , 47 ]. In October 2020, As Italy began to experience the impact of the second wave of the epidemic, the government introduced further actions and restrictions on social life. All hospital facilities had been upgraded and expanded, with more beds and intensive care units than in March 2020. Tracking applications, monitoring systems, and prediction systems were used to understand the progress of the outbreak. The Italian government forced the closure of gyms, swimming pools, theatres, and cinemas, as well as bars and restaurants by 6pm [ 48 ].

So far, there have been four outbreaks in Japan. The first wave occurred in January 2020, when COVID-19 was transmitted by a passenger from China [ 49 ]. A large cluster of infections was detected in March. The source of the second wave of transmission was a variant of the European virus, which Japanese experts believe was transmitted by travelers from Europe between March 11, 2020, and March 23, 2020. The third wave began in August 2020, when the number of confirmed cases in Japan reached 230,000 and the death toll surpassed 100,000. The fourth wave occurred in April 2021, and more than 4,000 new cases were confirmed, leading the Japanese government to declare a fourth wave.

Former U.S. President Donald Trump adopted a negative prevention and control policy, which led to the continuous expansion of the COVID-19 in the United States, and seriously affected production activities and economic development [ 50 ]. The United States has experienced at least three waves of the pandemic. The first wave was from March to July. The number of people diagnosed in the United States reached 50,000 during this period. The second wave appeared between July and October. The number of people diagnosed in the United States reached 100,000 during this period. The third wave began in October, with the number of confirmed cases rising rapidly to more than 200,000.

On November 5 th , Britain had to go into a second national lockdown because of a rise in cases and hospitalizations. After the blockade ended on 2 December, the number of cases began to rise again, with more than 70,000 deaths from COVID-19 as of 11 December 2020.On 4 January 2021, British Prime Minister Boris Johnson addressed the nation and announced the third blockade. Therefore, the UK was put into lockdown, more contagious variant of COVID-19 spread across the UK, causing a rapid increase in cases and deaths [ 51 ]. It is now reopening and coming out of lockdown.

Fig 2 shows the actual case fatality rate trends for the eight countries. It is not difficult to find in these eight countries, the CFR has a significant fluctuation. This confirms the validity of our empirical results. We believe that multiple factors are responsible for the cyclical fluctuation of the pandemic. Firstly, the COVID-19 virus has mutated. The mutation of the virus is difficult to control. The virus mutates to increase the rate of infection or death. UK COVID-19 virus mutation was first detected in samples collected last month in Kent during the UK COVID-19 pandemic in October 2020. Since then, its prevalence has doubled every 6.5 days. It has been associated with a significant increase in COVID-19 infection rates in the UK, partly due to the N501Y mutation. Some evidence shows that this variant has a 40–80% increased transmissibility [ 52 ]. 501.v2, 20 h / 501.y.V2 (formerly 20C/501Y.V2) and VOC-20Dec-02 (formerly VOC-202012/02) are tracked by the National Health Department in South Africa. The researchers found that the variant was higher in young people with no underlying health conditions, and it was more likely to cause serious disease in those cases than other variants [ 53 ]. Therefore, we believe that the effective measure to solve this problem is the acceleration of vaccine research and development and global sharing.

https://doi.org/10.1371/journal.pone.0267232.g002

Secondly, as the case fatality rate reaches the local minimum, the response level of governments of various countries will also decline. This results in a reduction in social distancing and an increase in public activities. Maintaining strict restrictions is the key to solving this problem.

Thirdly, in addition to the government and the virus, some people who do not wear masks in public places and hold public events in violation of restrictions are also important reasons for the repeated fluctuations of the pandemic. We believe that the government should strengthen the publicity and education of health knowledge. Only through the publicity and education of health knowledge can citizens realize the seriousness of COVID-19 and effectively restrain their actions. The use of masks and restrictions on social distance are important evidence of the government’s response. Easing restrictions would mean lowering the current level of epidemic control. First, according to our findings, if the government did not take timely measures to control the COVID-19 outbreak in the previous period, then the government will need to take more measures to control the development of COVID-19 in the current period. Thus, easing restrictions also means the government will have to pay more attention to containing the epidemic in the next period. This provides a powerful incentive for governments to tighten restrictions. Second, despite the restrictions imposed by the government, there may be a situation where citizens are unwilling to comply. It causes weak of the policy executive power. The weak policy executive power will produce the same effect with “doing nothing” policy, namely, it will also lead the government to pay more in the next period for epidemic control costs (in another paper, we used evolutionary game theory in detail discusses the punishment and reward mechanism in the restrictions for citizens and businesses). Therefore, the government must strengthen health science popularization and perfect the reward and punishment mechanism to make citizens abide by the restriction policy.

Compared with the existing literature, our research results extend the empirical evidence on the relationship between government response and COVID-19 in the literature. First, one of our main conclusions is that government response has a dynamic impact on the development of COVID-19, namely, the development of COVID-19 is influenced not only by the level of government response in the current period, but also by the response of the previous period. Existing literature confirms the positive impact of government response on the current development of COVID-19, but there is a lack of research on the dynamic impact. [ 54 ] studied how the response of the Ethiopian government suppressed COVID-19 in 2020. They found that containment of COVID-19 could be achieved through a combination of three public health measures: wearing masks, social distancing, and maintaining hygiene. Relaxing any of these three non-drug interventions could lead to a rebound in the number of new cases, they concluded. This rebound also supports our second main finding that government response and COVID-19 control show a cyclical relationship. Easing government restrictions could see a new wave of the epidemic shock. In the Ethiopian context, the most effective public health measure would be for urban populations to wear masks and rural populations to maintain social distance.

The positive role of the government response in suppressing the spread of COVID-19 is also reflected in the research conclusion of [ 55 ]. They examined the impact of major interventions in 11 European countries between the start of the COVID-19 pandemic in February 2020 and the start of the lockdown lifting on 4 May 2020. They used the semi-Mechanistic joint Bayesian Hierarchical model to show that the government’s lockdown measures had a huge impact on reducing transmission. They suggest that ongoing interventions should be considered to control the spread of COVID-19. This also supports our main finding: the cyclicality relationship between government response and COVID-19. We also recommend that sustained interventions are limited in curbing the spread of COVID-19 as the same with the suggestions given by [ 55 ]. [ 56 ] compared the time and severity of government response measures in the United States, Canada, China, Ethiopia, Japan, Kazakhstan, New Zealand, Singapore, South Korea, Vietnam, and Zimbabwe. It was found that in Vietnam, Zimbabwe, New Zealand, South Korea, Ethiopia, and Kazakhstan, early and strict implementation of a set of quarantines for infection, school closures, home isolation and restricted social gatherings reduced both the number of cases and the duration of transmission. In contrast, the United States has rarely implemented aggressive government responses rigorously or early. Their findings suggest that early implementation, consistent implementation, adequate time, and high compliance with government response measures are key factors in reducing the spread of COVID-19. [ 57 ] used a Bayesian hierarchical model to estimate the impact of non-pharmaceutical interventions on COVID-19 transmission in 41 countries. Some interventions are more effective than others, as for example the impact of different government restrictions on curbing the spread of COVID-19. This conclusion can make up the deficiency of this paper. We acknowledge that there is no further analysis of specific restrictive policies in this paper. We only analyzed the impact of government responses on the containment of COVID-19 in general. Therefore, the conclusion of [ 57 ] ’s study can provide a supplementary explanation for this paper. These findings suggest that by using effective interventions, some countries can control outbreaks without implementing stay-at-home orders. Through the interpretation of the above literature conclusions, our research conclusion added dynamic analysis on their basis. That is, the impact of government response on COVID-19 is intertemporal. This is an extension of the empirical evidence in the current literature.

Similarly, some relevant studies also support another conclusion of our research: government response and the development of COVID-19 show a cyclical relationship. [ 58 ] used Fourier transform to analyze the period and synchronicity of time series of COVID-19 infection cases and deaths. They found short and long-term changes in the COVID-19 development. The short period is 7 days. The cyclicality is thought to be caused by community social factors, joint diagnosis, and report cycle. They suggest optimizing infection control strategies by integrating spatial and temporal distances. [ 59 ] used spectral density of time series to assess the cycle of the number of coronavirus patients diagnosed each day, thus enabling the government to plan how to allocate resources more effectively. They found that their samples could distinguish between two types of cycles. The first type of cyclical fluctuation is 100 to 300 days. The time of the second type of cyclical fluctuation is about 7 days and the second type of cyclical fluctuation is related to the weekly cycle of population activities. For different countries, the stages of the seven-day fluctuation are consistent. Our study is an empirical extension of these two conclusions. We analyzed the cyclical relationship between government response and the development of COVID-19 based on the COVID-19 cycle.

This paper only analyzes the lag effect of government response on the development of COVID-19. [ 60 ] analyzed the causes of time lag through its impact on government expenditure. They argued that once a government has a clear expectation that restrictions will have to be implemented (the option of implementing them now is better than the option of postponing them). Thus, healthcare systems and cost-related variables have a significant impact on response times. Because expectations did not match reality and the government was too confident in its ability to fight the outbreak, it did not immediately implement restrictions. The associated economic costs have raised concerns about high economic costs. Overconfidence and cost concerns have delayed the implementation of restrictions, further increasing the overall cost of fighting the disease (because of the time lag, medical stress and containment costs are higher). Therefore, a rational government, once it is certain that they must impose restrictions, would obviously prefer to anticipate rather than delay.

5. Conclusion

Based on the long-term conditions, we used panel data by the dynamic GMM model to solve two research questions: 1. Does the government response affect the development of COVID-19 in the long run? 2. How does the government response affect the development of COVID-19 in the long run? Firstly, we demonstrate through empirical analysis that the government response significantly affects the development of the pandemic. We estimate the relevant parameters through four econometric methods. The results showed that the government response significantly affected the development of the pandemic.

Secondly, the government response has a cyclical effect on the development of COVID-19. As the government response increases, the COVID-19 case fatality rate will decrease, first, to a local minimum point, and will then increase to a local maximum point and finally converge to near 0. At the beginning, the government did not take corresponding measures (only a small number of people were infected at the beginning, so the government did not pay corresponding attention), and the COVID-19 case fatality rate was 0. When the number of infections and deaths increased to a certain level, the government began to realize the seriousness of the pandemic and began to respond. Potentially infected people and already infected people were constantly found, so the case fatality rate suddenly jumped from 0 to a local maximum value. With the continuous increase of government response policies, the case fatality rate decreased, COVID-19 was controlled to a certain extent, and the first wave of the pandemic ended. The mutation of the virus, the loosening of response policies and the lack of social distance among some citizens contributed to the arrival of the second wave. Therefore, the case fatality rate rose from a local minimum point to a local maximum point. Similarly, the case fatality rate will be completely controlled eventually after several rounds of government response (converging to near 0) on a global scale.

As we described in the section 4.4, a large number of facts and literature support our results. Our results are further extended on the basis of existing literature. First, from a dynamic perspective, we once again provide new empirical evidence for government responses to curb the spread of COVID-19. Existing literature provides detailed analysis of how government responses have influenced the development of COVID-19 (some have carefully analyzed the impact of specific government restrictive policies on COVID-19). In addition to confirming the validity of existing literature conclusions, our findings further analyze the intertemporal effects of government response on COVID-19. This is our biggest contribution.

In view of the above conclusions, we believe that the following policies can be implemented. Firstly, since the government response significantly affects the development of the pandemic, the government should improve the response level in the stage of case fatality rate increase. Secondly, the development of the pandemic tends to fluctuate periodically, and countries should be prepared to deal with COVID-19 in the long term. Thirdly, in the absence of exogenous shocks (vaccines), countries should adhere to strict response policies. Fourthly, in addition to the government response, increased publicity on the harm of COVID-19 would strengthen citizens’ capacity for self-restraint. Last but not least, governments should speed up the development of more effective COVID-19 vaccines and strengthen communication and cooperation in vaccine research and development. It is the global sharing of the vaccine that will ultimately allow humans to defeat COVID-19.

We have answered the key question of whether government responses affect the development of the pandemic over the long term, but we have not analyzed what causes the periodic fluctuations of the pandemic. Therefore, future research could be as follows: Firstly, in the intertemporal dynamics, which specific factors in the government response will affect the development of the pandemic? How much do these factors contribute to the development of the pandemic? Secondly, what are the changes after adding the vaccine variable? Vaccine, as a new variable, will greatly reduce (improve) the convergence time (speed) of case fatality rates. Therefore, the vaccine will have a significant impact on pandemic control. It will be an interesting research topic to study the mechanism of vaccine action on the development of the pandemic. Some scholars have made contributions to these issues [ 57 ].

Another key issue is that the citizens do not always follow the government’s restrictions. Therefore, whether citizens will comply with the government’s restrictions will be a key research issue. In subsequent studies, we used game theory to analyze under what circumstances citizens will comply with government restrictions and how governments should establish incentives and punishments to ensure compliance. The last important issue is the cost of government response. Sometimes the reason governments do not take sustained, response action is because of the high cost of COVID-19 control. How to balance government expenditure and citizen health is a promising research topic [ 60 ].

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A systematic literature review on existing digital government architectures: state-of-the-art, challenges, and prospects.

1. Introduction

2. related work, 3. research method, 3.1. planning the review, 3.1.1. review objectives and research questions.

• Describe what has been documented as a common understanding of Digital Government architectures;
• Identify Digital Government architecture characteristics, and existing associated challenges concerning the implementation of Digital Government infrastructure;
• Identify documented architecture building-blocks for establishing Digital Government infrastructure.

3.1.2. Search Strategy

• We screened for articles in the list of top journals and conference proceedings described by Levy and Ellis ( 2006 ).
• We use backward and forward reference searching as described by Webster and Watson ( 2002 ) which included searching for references cited in the articles and once certain articles were selected, they were further screened to identify other articles which cite them.

3.1.3. Inclusion and Exclusion Criteria

3.1.4. inclusion criteria:.

• The paper is peer-reviewed publication.
• The language of the study is English.
• The study is relevant to the given search criteria.
• The papers report an empirical study and are published in peer reviewed journals and/or conferences.
• The selected studies from all the above-listed databases were published during 2003–2020. We chose the databases for specific periods. In the databases, the number of retrieved articles varied. To have an average number of articles we filtered them by year. (such a time frame was chosen to as exhaustive as possible and not exclude essential papers).

3.1.5. Exclusion Criteria:

• Studies that do not address Digital Government and its architecture as a main focus of the research.
• Studies that do not discuss the challenges among existing Digital Government architecture.
• Articles that do not define or describe the Digital Government architecture.
• Studies that do not refer to architecture building blocks of Digital Government architecture.

3.2. Conducting the Review

3.2.1. study search and selection:, 3.2.2. data extraction and article classification.

• Title of the article
• Publication year
• Digital Government Model (What Digital Government Model does the architecture support?)
• Architectural pattern or style
• Quality attributes
• Technologies

4. Discussion of the Results

4.1. overview of studies, 4.2. existing architectures.

• RQ1: What are the existing forms of Digital Government architecture found through literature review?

4.3. Characteristics and Challenges

• RQ2: What are the characteristics of Digital Government architectures and the associated challenges?
• Interoperability and integration between data and applications ( AlAbdali et al. 2019 ; Defriani and Resmi 2019 ) and with various information systems ( Helali et al. 2011 ; Cellary and Strykowski 2009 ; Sedek et al. 2011 ).
• Having a secure architecture to ensure higher security of hardware and software to build trust with users ( Helali et al. 2011 ; Cellary and Strykowski 2009 ; Sedek et al. 2011 ).
• Adaptability to changing requirements that can have technical, socioeconomic, legal, and/or political nature Janssen ( 2007 ).
• Flexible integration of architecture’s components ( Helali et al. 2011 ; Sedek et al. 2011 ) to better align business processes and technologies Janssen et al. ( 2003 ).
• Reusability of components to be used in more than one system ( Mohamed et al. 2012 ; AlAbdali et al. 2019 ).
• Resilient to changes in the service environment Yan and Guo ( 2010 ).
• Compatibility of Digital Government architecture with the already existing infrastructure, such as legacy system and multiple public institutions integration in different environments Helali et al. ( 2011 ).
• Providing citizens the Single Sign-On (SSO) service through a standard interface or a single window for all electronic services offered by the public sector ( Drogkaris et al. 2010 ; Zeeshan Ali Ansari and Imran Khan 2008 ; Kaliontzoglou et al. 2005 ).
• Traceability of system operations performed by specific system users Helali et al. ( 2011 ).
• Usability i.e., providing functions that are required for better system performance ( Helali et al. 2011 ; Cellary and Strykowski 2009 ).
• Cross-border characteristics i.e., providing Digital Government services in an international context and managerial settings in terms of G2C and G2G Helali et al. ( 2011 ).
• Scalable to host a large number of digital services ( Helali et al. 2011 ; Sedek et al. 2011 ).
• Legality i.e., providing Digital Government services according to relevant legislation and judiciary Helali et al. ( 2011 ).
• Cost-effective i.e., The architecture should be implemented in a way that the deployment and operation resources are kept to a minimum ( Helali et al. 2011 ; Sedek et al. 2011 ; Cellary and Strykowski 2009 ).
• Technological neutrality: The architecture must ensure that no components included in its definition advocate specific suppliers Moreno et al. ( 2014 ).
• Platform independence: The architecture is not dependent on particular technology platform implementation nor assumes a particular technology Moreno et al. ( 2014 ).
• Minimal learning curve i.e., giving limited training to government employees to implement or use the architecture Helali et al. ( 2011 ).
• Comprehensibility: The architecture should be well-defined, and understandable with strategic clarity by the Digital Government leaders Agarwal et al. ( 2017 ).
• Citizen-Centric: The Architecture must be designed in a way to support the strengthening of the relationship between citizens and the government Moreno et al. ( 2014 ).

4.4. Basic Architecture Building Blocks

• RQ3: What are the basic architecture building blocks found in the Digital Government architectures?

5. Conclusions

5.1. limitations, 5.2. future work, author contributions, conflicts of interest, appendix a. search strings.

Appendix B. Comparison of Presented Digital Government Architectures Agains the Characteristics

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Baheer, B.A.; Lamas, D.; Sousa, S. A Systematic Literature Review on Existing Digital Government Architectures: State-of-the-Art, Challenges, and Prospects. Adm. Sci. 2020 , 10 , 25. https://doi.org/10.3390/admsci10020025

Baheer BA, Lamas D, Sousa S. A Systematic Literature Review on Existing Digital Government Architectures: State-of-the-Art, Challenges, and Prospects. Administrative Sciences . 2020; 10(2):25. https://doi.org/10.3390/admsci10020025

Baheer, Baseer Ahmad, David Lamas, and Sónia Sousa. 2020. "A Systematic Literature Review on Existing Digital Government Architectures: State-of-the-Art, Challenges, and Prospects" Administrative Sciences 10, no. 2: 25. https://doi.org/10.3390/admsci10020025

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Government structure.

Published on Mon, May 17, 2021 9:00AM PDT | Updated Tue, August 8, 2023 11:23AM PDT

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The US is a constitutional republic and representative democracy. Our Government is regulated by a system of checks and balances defined by the US Constitution, which serves as the country’s supreme legal document. In the US, citizens are usually subject to three levels of government: federal, state, and local. The original text of the Constitution establishes the structure and responsibilities of the federal government and its relationship with the individual states. The Constitution has been amended 27 times, including the first 10 amendments, the Bill of Rights, which forms the central basis of Americans’ individual rights.

Federal government structure

The Constitution divides the federal government into three branches to ensure a central government in which no individual or group gains too much control:

• Legislative – Makes laws (Congress)
• Executive – Carries out laws (President, Vice President, Cabinet)
• Judicial – Evaluates laws (Supreme Court and other courts)

Each branch of government can change acts of the other branches as follows:

• The president can veto legislative bills passed by Congress before they become law (subject to Congressional override).
• Congress confirms or rejects the president’s appointments and can remove the president from office in exceptional circumstances.
• The justices of the Supreme Court, who can overturn unconstitutional laws, are appointed by the president and confirmed by the Senate.

Legislative

The legislative branch enacts legislation, confirms or rejects presidential appointments, and has the authority to declare war. This branch comprises Congress (the Senate and House of Representatives) and several agencies that provide support services to Congress.

The executive branch carries out and enforces laws. It includes the president, vice president, the Cabinet, 15 executive departments, independent agencies, and other boards, commissions, and committees.

The judicial branch interprets the meaning of laws, applies laws to individual cases, and decides if laws violate the Constitution. The judicial branch comprises the Supreme Court and other federal courts.

THE UNITED STATES GOVERNMENT

THE CONSTITUTION

SIGNIFICANT REPORTING ENTITIES (15)

OTHER SIGNIFICANT REPORTING ENTITIES

IN CONSERVATORSHIP

Fannie Mae              Freddie Mac

For a discussion of each of the federal government departments and offices, please see The United States Government Manual at https://www.govinfo.gov/app/collection/GOVMAN .

State government structure 1

Under the Tenth Amendment to the US Constitution, all powers not granted to the federal government are reserved to the states and the people. All state governments are modeled after the federal government and consist of three branches: executive, legislative, and judicial. The US Constitution mandates that states uphold a “republican form” of government, although the three-branch structure is not required.

All 50 states have legislatures made up of elected representatives, who consider matters brought forth by the governor or introduced by its members to create legislation that becomes law. The legislature also approves a state’s budget and initiates tax legislation and articles of impeachment. The latter is part of a system of checks and balances among the three branches of government that mirrors the federal system and prevents any branch from abusing its power.

Every state except one has a bicameral legislature made up of two chambers: a smaller upper house and a larger lower house. Together the two chambers make state laws and fulfill other governing responsibilities. The smaller upper chamber is always called the Senate, and its members generally serve longer terms, usually four years. The larger lower chamber is most often called the House of Representatives, but some states call it the Assembly or the House of Delegates. Its members usually serve shorter terms, often two years. Nebraska is the lone state that has just one chamber in its legislature.

In every state, the executive branch is headed by a governor who is directly elected by the people. In most states, other leaders in the executive branch are also directly elected, including the lieutenant governor, the attorney general, the secretary of state, and auditors and commissioners. States reserve the right to organize in any way, so they often vary greatly with regard to executive structure. No two state executive organizations are identical.

Most states have a supreme court that hears appeals from lower-level state courts. Court structures and judicial appointments/elections are determined either by legislation or by the state constitution. The state supreme court usually focuses on correcting errors made in lower courts and therefore holds no trials. Rulings made in state supreme courts are normally binding; however, when questions are raised regarding consistency with the US Constitution, matters may be appealed directly to the United States Supreme Court.

STATE GOVERNMENTS (50)

Local government structure 2

A government is an organized entity that, in addition to having governmental character, has sufficient discretion in the management of its own affairs to distinguish it as separate from the administrative structure of any other governmental unit.

To be counted as a government, any entity must possess all three of the following attributes:

• Existence as an organized entity – the presence of some form of organization and the possession of some corporate powers, such as perpetual succession, the right to sue and be sued, have a name, make contracts, acquire and dispose of property, and the like.
• Governmental character – In essence, an organization can only be considered to be a government if it provides services, wields authority, or bears accountability that is of a public nature.
• Substantial autonomy – This requirement is met when, subject to statutory limitations and any supervision of local governments by the state, an entity has considerable fiscal and administrative independence.

LOCAL GOVERNMENTS (90,075)

Insular area government structure

The US has many insular areas, or jurisdictions that are neither a state nor a federal district, including any commonwealth, freely associated state, possession, or territory. Five of the insular areas – Puerto Rico, Guam, Northern Mariana Islands, US Virgin Islands, and American Samoa – are self-governing, each with a non-voting member of the House of Representatives and permanent populations. The remaining areas are small islands, atolls, and reefs in the Pacific Ocean and Caribbean Sea. US possession of certain of these areas is disputed by other countries. The population of these areas are excluded from our reported population figures. However, these individuals may contribute to the revenues, expenditures, and other figures included in this report.

American Indian tribal government structure

Our Government officially recognizes 574 Indian tribes in the contiguous 48 states and Alaska. The US observes tribal sovereignty of the American Indian nations to a limited degree, as it does with the states’ sovereignty. American Indians are US citizens and tribal lands are subject to the jurisdiction of the US Congress and the federal courts. Like the states, the tribal governments have a great deal of autonomy with respect to their members, including the power to tax, govern, and try them in court, but also like the states, tribes are not allowed to make war, engage in their own foreign relations, or print and issue currency.

Continue exploring

Item 1 - purpose and function of our government - general, government operations, explore the 2021 government 10-k, introduction, about this report, item 1a. risk factors, item 2. properties, item 3. legal proceedings, item 6. selected financial data, item 7. management’s discussion and analysis of financial condition and results of operations, item 7a. quantitative and qualitative disclosures about market risk, item 8. financial statements and supplementary data, item 9a. controls and procedures, item 10. executive officers and governance, item 11. executive officer compensation, item 13. certain relationships and related transactions, and director independence, item 15. exhibits, sign up for the newsletter.

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