Official Projections Research Articles

Policy steps in the federal budget and health care to achieve sustainable fiscal conditions in the U.S.

Health care spending has grown significantly in the US, and is a major cause of rising federal deficits. Official projections find that low economic growth and aging of the population will lead to a modest continuation of this situation, but they miss that labor shortages have a particular impact on inefficient sectors, raising the cost of health care. We develop a unified macroeconomic model to address this shortcoming, with key variables—particularly in the health care sector and interest rates—endogenously determined. We find that the current fiscal trajectory of the US is unsustainable, with future deficits and debt well beyond both historical norms and official projections. Policy steps, focusing on reducing health care spending, increasing capital, and fiscal retrenchment, can lead to sustainable fiscal conditions and raise living standards that will otherwise fall.

Strategies toward an effective and sustainable energy transition for Cuba

This study evaluated the possibilities of energy transition in Cuba 2030. Cuba is currently in a vulnerable energy situation since it strongly depends on the importation of fossil energy. Strategies based on intermittent RES (solar and wind) can reduce this vulnerability, but the introduction of this type of source impacts the energy system's characteristics and aspects at a country/regional scale. Most of the studies about energy transition strategies focus on the evaluation of a few specific arbitrary scenarios or the classic economic optimization approach. This research relies on existing methods to evaluate energy scenarios. However, some aspects of our approach are original: differently to the comparison of arbitrary scenarios we evaluate a fairly large number of scenarios, and differently to the classic optimization we consider many different indicators (e.g., energy security, carbon footprint, air quality, and economic). This allows the description of the trends of the changes in the energy system and the evaluation of the benefits linked to a progressive introduction of intermittent sources. Scenarios for Cuba correspond to a progressive introduction of intermittent sources to reduce fossil fuel importation. These scenarios were compared with the official projection of the Cuban government for 2030 showing that the introduction of solar and wind improve the situation of the island by reducing CO2 emissions, improving air quality, and generating economic benefits. Monetizing the CO2 emissions results in greater economic benefits through carbon compensation. Furthermore, replacing Internal Combustion Vehicles (ICVs) with Electric Vehicles (EVs) could offer additional benefits across all these aspects.

Tuberculosis incidence in Brazil: time series analysis between 2001 and 2021 and projection until 2030.

To assess the incidence of tuberculosis in Brazil between 2001 and 2022 and estimate the monthly incidence forecast until 2030. This is a time-series study based on monthly tuberculosis records from the Notifiable Diseases Information System and official projections of the Brazilian population. The monthly incidence of tuberculosis from 2001 to 2022 was evaluated using segmented linear regression to identify trend breaks. Seasonal autoregressive integrated moving average (Sarima) was used to predict the monthly incidence from 2023 to 2030, deadline for achieving the sustainable development goals (SDGs). There was a decrease in incidence between January/2001 and December/2014 (4.60 to 3.19 cases-month/100,000 inhabitants; β=-0.005; p<0.001), followed by an increase between January/2015 and March /2020 (β=0.013; p<0.001). There was a sharp drop in cases in April/2020, with the onset of the pandemic, and acceleration of the increase in cases since then (β=0.025; p<0.001). A projection of 124,245 cases in 2030 was made, with an estimated incidence of 4.64 cases-month/100,000 inhabitants, levels similar to those in the 2000s. The Sarima model proved to be robust, with error of 4.1% when removing the pandemic period. The decreasing trend in tuberculosis cases was reversed from 2015 onwards, a period of economic crisis, and was also impacted by the pandemic when there was a reduction in records. The Sarima model can be a useful forecasting tool for epidemiological surveillance. Greater investments in prevention and control need to be made to reduce the occurrence of tuberculosis, in line with the SDGs.

Research on Xinjiang Tourism Image Perception and Official Projection Image Based on Network Text Analysis

Research on Xinjiang Tourism Image Perception and Official Projection Image Based on Network Text Analysis

Analysis of Discrepancies Between Destination Image and Tourists' Perceived Image: Taking Fuzhou as a Case

Taking Fuzhou as a case study, this research analyzes tourist network travel notes, online comments, and official website reports of the tourism bureau, and uses the word frequency statistical function of semantic analysis software to extract high-frequency words of tourist perception and official website projection of tourism image, and constructs social relations and semantic networks to compare and analyze tourist perception and official website dissemination of tourism image. The research results show that the Fuzhou tourism image perceived by tourists can be summarized into four dimensions: tourist attractions, tourism environment atmosphere, tourism facilities and services, and tourism experience. Tourists perception of tourist attractions is consistent with the official projection, and Sanfang Qixiang and hot springs have become representative resources of Fuzhou. The key points of official propaganda are inconsistent with the focus of tourist perception. The Fuzhou Tourism Bureau should pay more attention to tourism hotspots such as historical buildings in the city and Pingtan Island scenery, and actively create an ecological leisure city, focusing on parent-child study tours and rural revitalization. Tourists prefer historical buildings in the city and Pingtan Island scenery. Finally, based on the research conclusions, targeted suggestions are proposed for Fuzhous tourism promotion.

Accuracy of Local Authority Population Forecasts Produced by a New Minimal Data Model: A Case Study of England

The preparation of forecasts for small and local area populations involves many challenges. Standard cohort-component models are problematic because of small numbers, which make estimation of rates unreliable. Because of this, the Synthetic Migration Population Projection (SYMPOPP) model was designed to forecast local populations without need for detailed area-specific information. This model had been used successfully for small area forecasts in Australia. The objective of the paper is to assess its performance when applied to local areas in England. The model uses a bi-regional structure based on a movement population account. Sub-models of total population change are employed to control future change. Fertility, mortality and migration rates are borrowed from national statistics, constrained to small area indicators. The model uses an Excel workbook with VBA routines and is relatively easy and quick to use. Model inputs were calibrated for 2006–2011 and used to forecast for 2011–2021. Results were tested against the census-based 2021 mid-year populations. A new error statistic, Age Structure Error, was used to evaluate Basic and Refined model versions against official projections. The two versions of SYMPOPP posted lower errors. The simple models had fewer areas with errors of 10% or more (12.3–12.6%) compared with the official projections (14.5% of areas). Investigation revealed that these errors occurred in local authorities with high military, student, prison, or ethnic minority populations, influenced by factors not captured in a projection model for the general population.

Study of channel upgrades and ship choices of river-shipping of port access-transportation

This study builds a bi-level programming model to optimize river channel upgrades and liner operation, while minimizing the total cost of container transportation to ports. The upper model determines the optimal channel upgrades, choice of liner size, and liner operating frequency. The sum of the trucking freight, the river liner shipping cost, the CO2 tax payment, and the depreciation of the investments in channel upgrades and ship purchases is calculated based on official projections of freight demand over 30 years. The lower model determines the optimal container routes. A case study of Zhejiang Province shows that Qiantang River and Hangzhou-Ningbo Canal should be upgraded from Level Ⅳ to Level III waterways, while the Meihu and Zhajiasu Lines should be upgraded from Level Ⅴ to Level IV waterways. Due to these improvements, the mode share of river shipping is projected to increase to 30%, while CO2 emissions from container port access transportation are estimated to decrease by 23.5 million tons over 30 years.

Экономика форс-мажора: цена «финансовой стабильности»

In this paper, it is shown that, despite a tremendous number of sanctions that significantly modify the conditions of financial and economic equilibrium in Russia, the basic mechanisms, priorities and construction of the goals of the financial and economic policy have not changed. This is especially true for monetary and fiscal policy. The analysis of the parameters and results of budget planning for 2022–2023 has been carried out. Although there are no catastrophic failures of macroeconomic indicators according to the Ministry of Finance in 2022 and the official projections of the 2023 budget do not promise an increase in problems, the discrepancy between the actual possibilities to increase revenues and the imperative requirements to increase budget expenditures signal a serious deterioration of the budget situation, which requires urgent and adequate solutions. The author discusses the prospect of the state budget deficit turning into a permanent phenomenon accompanying the country’s economic development for a long period, due to the indefinite period of revenue suppression and acceleration of state budget expenditures, the reasons of which are long military expenditures and the duration of restructuring the structure and mechanisms of global and subglobal financial and economic interactions. In this paper, estimates of the budget deficit, which are alternative to the official data, have been made; estimates of real sizes and dynamics of budget deficits are proposed; and the concept of hierarchy and target concentration of budget expenditures is argued. The main tools for financing budget deficits (the National Welfare Fund, ruble devaluation, money emission, government borrowings) are analyzed, the possibilities and potential limits of their use are shown. It is shown that all of them, except domestic government borrowings, give a short-term effect and at the same time have a negative impact on macroeconomic equilibrium. The possibilities, direct and indirect consequences of the policy of reduction of budget expenditures are considered

Assessing the Accuracy of National Population Projections

Few producers of official population projections provide regular evaluations of past projection inaccuracies. This paper assesses deviations between the projected and registered total population for Norway (1996–2018), as well as deviations in the age structure, total fertility rate and number of births, period life expectancy at birth and number of deaths, and net international migration. Projected life expectancy was consistently lower than the real development. Few systematic deviations were observed for fertility up to 2009, but thereafter fertility has been consistently overprojected. However, the deviations between projected and realised trends in births and deaths have been relatively small as compared to those for net international migration. The projections produced between 1996–2005 underestimated long-term population growth due primarily to the unforeseen increase in immigration following EU expansion in 2004. More recent projections contain no consistent under- or overprojection of net migration and the deviations for the total population have been moderate.

An Open‐Source Model for Projecting Small Area Demographic and Land‐Use Change

The size, composition, and spatial distribution of both people and households have a substantial impact on the demand for and development and delivery of infrastructure required to support the population. Infrastructure encompasses a wide range of domains including energy, transport, and water, each of which has its own set of spatial catchments at differing scales. Demographic projections are required to assess potential future demand; however, official projections are usually not provided at a high level of spatial resolution required for infrastructure planning. Furthermore, generating bespoke demographic projections, often incorporating a range of scenarios of possible future demographic change is a specialist, resource intensive job and as such is often missing from infrastructure development projects. In this paper we make the case that such demographic projections should be at the heart of infrastructure planning and present a set of open‐source models which can be used to undertake this demographic projection work, thus providing the tools needed to fill the identified gap. We make use of a case study for the United Kingdom to exemplify how a range of scenarios can be assessed using our model.

Disease Burden Estimation of Lymphatic Filariasis in an Endemic Area.

Background: Anecdotal evidence collected by a community organization suggested high prevalence of lymphatic filariasis (LF) in Sitapur district, Uttar Pradesh. Village volunteers subsequently conducted a line listing in 13 villages of Pisawan block and recorded 261 cases of known LF complications, namely hydrocele and lymphedema. This being far higher than official projections, a block-wide cluster survey was conducted to estimate the disease burden more accurately. Methods: Cluster sampling techniques were applied, and 41 clusters selected within Pisawan block. Survey teams comprising one woman and man interviewed member of all households in the cluster, recording details of individuals suffering from hydrocele or lymphedema within them. Age and gender were noted, as well as duration of symptoms and details of any treatment availed. Results: A total of 1851 patients (1256 males and 595 females) were reported to have lymphedema, hydrocele, or both in the 6931 households surveyed. This equates to a prevalence rate of 4.95% (with 9.75% margin of error) in Pisawan block. With these calculations, an estimated 11,049 + 1077 patients with LF complications in Pisawan block, Sitapur, UP in 2016. Conclusions: The high prevalence rate of LF complications in Pisawan block is disconcerting, especially considering India's commitment to eliminate LF by 2020. Compliance with Mass Drug Administration (MDA) must be improved. Furthermore, the Morbidity Management and Disability Prevention (MMDP) component of the National Programme for Elimination of Lymphatic Filariasis (PELF) must be strengthened so that such patients can lead a productive life.

Assessing the renewable energy policy paradox: A scenario analysis for the Italian electricity market

The renewable energy policy paradox states that the combination of liberalized markets with low marginal cost and intermittent technologies tends to reduce electricity prices and, hence, the profitability of new investments in wind and solar energy, thus rendering price-incentive policies less effective or more costly. Most simulation models are not suited to assess the feasibility of middle and long-term goals under the price policies already in place. To fill this gap, this study applies a novel hybrid top-down-bottom-up dynamic macrosimulation model to the Italian economy (2015–2040). To incorporate uncertainty about the future costs of generation and storage technologies, fossil fuel prices, demand elasticities, macroeconomic performance and price incentives, we rely on exploratory model analysis to build scenarios from three clusters out of the 1000 different simulations. Our results suggest a decreasing trend in electricity prices in contrast to the latest official projections. Accordingly, the expansion of renewable energy slows down and none of the 1000 simulations reach the 2030 target of 55% renewable energy in electricity supply. Despite the ineffectiveness of the price subsidy policy in the first ten years (2021–2030), it is still crucial to reach very high penetration of variable renewable energy sources by 2040.

Probabilistic population projections for provincial levels in Indonesia

This research aims to produce a probabilistic population projection for the provincial level in Indonesia. The base population uses the base population used by Bappenas, BPS, and UNFPA Indonesia in compiling the 2015-2045 Indonesian official population projection. One thousand trajectories of future E0 values are projected using JPP with Asian countries as the prior distribution, while 1,000 trajectories of future TFR values are projected using BHM-based projections with Asian countries as the prior distribution. Meanwhile, the number and pattern of net internal migration are assumed to be constant during the projection period. The calculation process uses the bayesPop package in R software. The projection results show that the total population of the official projection is located at the predicted interval of the Bayesian population projection, except for the Kepulauan Riau.

Disaggregation of official demographic projections in sub-groups by education level: the neglected \u201ccomposition effect\u201d in the future path of life expectancy

We developed an innovative method to break down official population forecasts by educational level. The mortality rates of the high education group and low education group were projected using an iterative procedure, whose starting point was the life tables by education level for Italy, based on the year 2012. We provide a set of different scenarios on the convergence/divergence of the mortality differential between the high and low education groups. In each scenario, the demographic size and the life expectancy of the two sub-groups were projected annually over the period 2018–2065. We compared the life expectancy paths in the whole population and in the sub-groups. We found that in all of our projections, population life expectancy converges to the life expectancy of the high education group. We call this feature of our outcomes the “composition effect”, and we show how highly persistent it is, even in scenarios where the mortality differential between social groups is assumed to decrease over time. In a midway scenario, where the mortality differential is assumed to follow an intermediate path between complete disappearance in year 2065 and stability at the 2012 level, and in all the scenarios with a milder convergence hypothesis, our “composition effect” prevails over the effect of convergence for men and women. For instance, assuming stability in the mortality differential, we estimated a life expectancy increase at age 65 of 2.9 and 2.6 years for men, and 3.2 and 3.1 for women, in the low and high education groups, respectively, over the whole projection period. Over the same period, Italian official projections estimate an increase of 3.7 years in life expectancy at age 65 for the whole population. Our results have relevant implications for retirement and ageing policies, in particular for those European countries that have linked statutory retirement age to variations in population life expectancies. In all the scenarios where the composition effect is not offset by a strong convergence of mortality differentials, we show that the statutory retirement age increases faster than the group-specific life expectancies, and this finding implies that the expected time spent in retirement will shrink for the whole population. This potential future outcome seems to be an unintended consequence of the indexation rule.

Regional concentration of higher education

This research article focuses on the regional concentration of higher education. The purpose of the research is to examine the effects of this concentration and to devise some possible outcomes and implications for the regional economic growth and development. We discuss the endogeneity of higher education and evaluate the differences such as the official demographic projections or the growth-related factors, including student numbers predicted by official statisticians. Our article contributes to ongoing research on the role of higher education in promoting regional economic development and emerging inequalities in the regions around the world. In addition, it focuses on the existence of the multiple channels of activity through which tertiary education institutions (TEIs) benefit their regional economies. In addition, the paper tackles the issue of regional concentration of TEIs within and across regions and clearly demonstrates how the geography of higher education has evolved and developed in the recent years.

The COVID-19 Shock and Challenges for Time Series Models

We document the impact of COVID-19 on frequently employed time series models, with a focus on euro area inflation. We show that for both single equation models (Phillips curves) and Vector Autoregressions (VARs) estimated parameters change notably with the pandemic. In a VAR, allowing the errors to have a distribution with fatter tails than the Gaussian one equips the model to better deal with the COVID-19 shock. A standard Gaussian VAR can still be used for producing conditional forecasts when relevant off-model information is used. We illustrate this by conditioning on official projections for a set of variables, but also by tilting to expectations from the Survey of Professional Forecasters. For Phillips curves, averaging across many conditional forecasts in a thick modelling framework offers some hedge against parameter instability.

Energy Demand Forecasting: Avoiding Multi-collinearity

As having one of the major economies and rising population, Turkey’s energy demand is increasing substantially. The main objective of this research was to apply ridge regression to estimate Turkey’s primary energy consumption. Gross domestic product, population, automobile ownership, export and import rates, manufacturing and electricity consumption values of the country were involved in the forecasting model as independent variables. Although regression models end up closer estimates to the real values, having multi-collinearity between variables makes those models unreliable. Therefore, other techniques such as time series, artificial neural networks and genetic algorithms have been tried and performed better than regression models. Ridge regression, a rarely applied and underappreciated model in the literature, is used to overcome the multi-collinearity problem which means high correlation among independent variables. In this study, the ridge regression technique was compared with time series methods and artificial neural networks. The principal results showed that ridge regression is better to estimate energy demand and gave lower mean squared error than other techniques (16.51 for ridge regression followed by 19.00 for neural network). Moreover, estimated values were also found closer to the real energy demand than official projections of the Ministry (only 5% deviation with the proposed model, while official projections occurred by 20% error). Since the accurate forecasting of energy demand is significant for the proper policy design, the best methodology should be opted for and ridge regression seems one of those alternative techniques. In addition, the easiness of the ridge regression makes it applicable to several forecasting methods.

Mortality Attributed to COVID-19 in High-Altitude Populations

Woolcott, Orison O., and Richard N. Bergman. Mortality attributed to COVID-19 in high-altitude populations. High Alt Med Biol. 21:409-416, 2020. Background: Since partial oxygen pressure decreases as altitude increases, environmental hypoxia could worsen Coronavirus Disease 2019 (COVID-19) patient's hypoxemia. We compared COVID-19 mortality at different altitudes. Methods: Retrospective analysis of population-level data on COVID-19 deaths was conducted in the United States (1,016 counties) and Mexico (567 municipalities). Mixed-model Poisson regression analysis of the association between altitude and COVID-19 mortality was conducted using individual-level data from 40,168 Mexican subjects with COVID-19, adjusting for multiple covariates. Results: Between January 20 and April 13, 2020, mortality rates were higher in U.S. counties located at ≥2,000 m elevation versus those located <1,500 m (12.3 vs. 3.2 per 100,000; p < 0.001). In Mexico, between March 13 and May 13, 2020, mortality rates were higher in municipalities located at ≥2,000 m versus those located <1,500 m (5.3 vs. 3.9 per 100,000; p < 0.001). Among Mexican subjects younger than 65 years, the risk of death was 36% higher in those living at ≥2,000 m versus those living at <1,500 m (adjusted incidence rate ratio [IRR]: 1.36; confidence interval [95% CI], 1.05-1.78; p = 0.022). Among Mexican men, the risk of death was 31% higher at ≥2,000 m versus that at <1,500 m (adjusted IRR: 1.31; 95% CI, 1.03-1.66; p = 0.025). No association between altitude and COVID-19 mortality was found among Mexican women or among Mexican subjects 65 years of age and older. Conclusions: Altitude is associated with COVID-19 mortality in men younger than 65 years.

Public Inference from Crisis Policy: Evidence from the COVID-19 Pandemic

Governments often provide inconsistent guidance to the public. Does inconsistency affect how much people believe the latest recommendations? Using an incentivized online experiment with 1,900 US respondents in early April 2020, we present all participants with the latest official projection about coronavirus death counts. We randomize exposure to information that highlights the government’s inconsistency about the coronavirus threat. When inconsistency is salient, participants have reduced propensity to revise prior beliefs about death counts and lower self-reported trust in the government. These results align with a simple model of signal extraction from government communication, and have implications for the design of changing guidelines in other settings.

Government fiscal projection and debt sustainability

This paper reconsiders Japan’s fiscal sustainability. We investigate whether a simulation conducted under the political constraint imposed by a fiscal reaction function supports the official projection. First, we obtain Japan’s fiscal reaction function by estimating the response of the primary surpluses to the past debt for a panel data set of 23 OECD countries. Next, we investigate the political feasibility of the official projection using our estimated reaction function. When the Cabinet Office criterion is used for the debt-to-GDP ratio, the government can attain the policy target of nonnegative fiscal surpluses and realize fiscal sustainability. Notably, the negative growth-adjusted bond yield and the high growth rate contribute to this finding.