Political Budget Cycles in Local Governments

2012 ◽  
Vol 10 (4) ◽  
Author(s):  
Bernardino Benito ◽  
Francisco Bastida ◽  
Cristina Vicente
Keyword(s):  
Time Series ◽  
Local Governments ◽  
Political Orientation ◽  
Municipal Governments ◽  
Political Budget Cycles ◽  
Long Time Series ◽  
Capital Spending ◽  
Long Time ◽  
The Impact ◽  
Budget Cycles

This paper aims to analyse the impact of the electoral schedule on municipal governments’ financial activities. Specifically, we pay attention to capital spending, current spending and taxes. We use a long time series (1989-2008) of the 45 municipalities of the Region of Murcia (Spain). Our results show the existence of Political Budget Cycles on capital spending and taxes. We find an increase of capital spending in the electoral and pre-electoral years, when the impact is higher on voters. Taxes are reduced in the election year. We also prove that the mayor’s political orientation and political strength impact Political Budget Cycles. The mayor’s decision of running for re-election does not affect the magnitude of the cycle.

scholarly journals Using the results of a nationwide phenological network to examine the impact of changes in phenology of plant species on the concentration of plant pollen in the air

2012 ◽  
Vol 63 (2) ◽  
pp. 69-74
Author(s):  
Katarzyna Jabłońska ◽  
Piotr Rapiejko
Keyword(s):  
Time Series ◽  
Pollen Season ◽  
Growing Season ◽  
Meteorological Conditions ◽  
Pollen Data ◽  
Time Pattern ◽  
Phenological Data ◽  
Long Time Series ◽  
Long Time ◽  
The Impact

The application of phenological data together with meteorological and pollen data in a comprehensive analysis gives an opportunity to draw conclusions on variability of the starting date of the pollen season and its dynamics in terms of meteorological factors. It is quite important especially due to the fact that studies conducted all over Europe have proved that species phenology responds to climate warming trends. There has been observed a tendency to an earlier onset of spring flowering and leafing as well as the lengthening of the growing season. Although phenological network studies differ with regard to regions, species, events observed and applied methods, their data show a clear temperature-driven extension of the growing season by up to 2 weeks in the second half of the 20th century in mid- and high northern latitudes; for example, in Germany changes in timing of phenological spring events have been estimated at about -1.6 days / decade, while in Switzerland: -2.3 days / decade. Despite interannual variability in flowering date, caused by specific meteorological conditions each year, long-time series of phenological data from the area of Poland have proved that hazel flowering occurred in the surroundings of Warsaw later in the 50's (third decade of March) than it is observed at the beginning of the 21st century (second decade of March). There is a lack of such long time series of pollen data, but we can suspect that the hazel pollen season has changed similarly to the time pattern of its flowering. Plants are very sensitive to weather conditions, therefore it is important to know as precisely as possible the impact of meteorological conditions on a plant's reactions. The determination of thermal thresholds for a specific plant's reactions may be beneficial for this purpose. The estimated value of Positive Degree Days (PDD> 50), which caused the first <i>Corylus</i> flowers (F2 phenophase) to bloom in the study years, requires testing in future years to make the threshold values credible.

The Impact of modern Tobacco Agriculture planning on the Spatio-temporal Evolution of Urban construction Land

2021 ◽  
Vol 7 (5) ◽  
pp. 938-949
Author(s):  
Miao Yahui ◽  
Jiang Ce ◽  
Gu Zifan ◽  
Xi Zenglei
Keyword(s):  
Time Series ◽  
Temporal Evolution ◽  
Market Demand ◽  
Continuous Growth ◽  
Construction Land ◽  
Long Time Series ◽  
Urban Construction ◽  
Long Time ◽  
Spatio Temporal ◽  
The Impact

In recent years, the world tobacco industry has shown a trend of continuous growth in market demand and increasingly concentrated tobacco market, which brings new opportunities to the tobacco agriculture development. However, the modern tobacco agriculture is bound to occupy a large amount of agricultural land, which will have a certain impact on the distribution of urban construction land (UCL). Therefore, reasonable and effective modern tobacco agricultural planning plays a vital role in promoting modern agricultural and urban development.In this paper, we took Baiyangdian basin as the study area, applying the long time series nighttime light (NTL) data to extract UCL and analysing the impact of modern tobacco agriculture planning on the spatio-temporal evolution of UCL. Firstly, we used a power function model to fit the two kinds of international mainstream NTL data to form a long time series NTL dataset from 1992 to 2018 to make the NTL data comparable over a long time. Then, the threshold segmentation method based on land use data calibration was applied to extract the UCL in Baiyangdian basin in 2000, 2010 and 2018, and to analyze its spatio-temporal evolution characteristics and patterns by combining the landscape metrics and gravity model. The results show that the UCL in Baiyangdian basin shows the expansion trend centered on the main urban area of Baoding City, land intensification degree has increased, and the modern tobacco agriculture planning has a profound impact on the spatio-temporal distribution of UCL. Our study will provide technical support and experience for the scientific modern tobacco agriculture planning.

scholarly journals Sea Ice Concentration Products over Polar Regions with Chinese FY3C/MWRI Data

2021 ◽  
Vol 13 (11) ◽  
pp. 2174
Author(s):  
Lijian Shi ◽  
Sen Liu ◽  
Yingni Shi ◽  
Xue Ao ◽  
Bin Zou ◽  
...  
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Ocean Circulation ◽  
The Arctic ◽  
Retrieval Algorithm ◽  
Atmospheric Effects ◽  
Observation Data ◽  
Long Time Series ◽  
Ice Concentration ◽  
Long Time

Polar sea ice affects atmospheric and ocean circulation and plays an important role in global climate change. Long time series sea ice concentrations (SIC) are an important parameter for climate research. This study presents an SIC retrieval algorithm based on brightness temperature (Tb) data from the FY3C Microwave Radiation Imager (MWRI) over the polar region. With the Tb data of Special Sensor Microwave Imager/Sounder (SSMIS) as a reference, monthly calibration models were established based on time–space matching and linear regression. After calibration, the correlation between the Tb of F17/SSMIS and FY3C/MWRI at different channels was improved. Then, SIC products over the Arctic and Antarctic in 2016–2019 were retrieved with the NASA team (NT) method. Atmospheric effects were reduced using two weather filters and a sea ice mask. A minimum ice concentration array used in the procedure reduced the land-to-ocean spillover effect. Compared with the SIC product of National Snow and Ice Data Center (NSIDC), the average relative difference of sea ice extent of the Arctic and Antarctic was found to be acceptable, with values of −0.27 ± 1.85 and 0.53 ± 1.50, respectively. To decrease the SIC error with fixed tie points (FTPs), the SIC was retrieved by the NT method with dynamic tie points (DTPs) based on the original Tb of FY3C/MWRI. The different SIC products were evaluated with ship observation data, synthetic aperture radar (SAR) sea ice cover products, and the Round Robin Data Package (RRDP). In comparison with the ship observation data, the SIC bias of FY3C with DTP is 4% and is much better than that of FY3C with FTP (9%). Evaluation results with SAR SIC data and closed ice data from RRDP show a similar trend between FY3C SIC with FTPs and FY3C SIC with DTPs. Using DTPs to present the Tb seasonal change of different types of sea ice improved the SIC accuracy, especially for the sea ice melting season. This study lays a foundation for the release of long time series operational SIC products with Chinese FY3 series satellites.

scholarly journals Performance stability of the MODIS and VIIRS LAI algorithms inferred from analysis of long time series of products

2021 ◽  
Vol 260 ◽  
pp. 112438
Author(s):  
Kai Yan ◽  
Jiabin Pu ◽  
Taejin Park ◽  
Baodong Xu ◽  
Yelu Zeng ◽  
...  
Keyword(s):  
Time Series ◽  
Long Time Series ◽  
Long Time

Cloud Properties over the North Slope of Alaska: Identifying the Prevailing Meteorological Regimes

2012 ◽  
Vol 25 (23) ◽  
pp. 8238-8258 ◽  
Author(s):  
Johannes Mülmenstädt ◽  
Dan Lubin ◽  
Lynn M. Russell ◽  
Andrew M. Vogelmann
Keyword(s):  
Time Series ◽  
Climate Model ◽  
North Slope ◽  
Test Cases ◽  
Synoptic Scale ◽  
Long Time Series ◽  
The North ◽  
Cloud Properties ◽  
North Slope Of Alaska ◽  
Long Time

Abstract Long time series of Arctic atmospheric measurements are assembled into meteorological categories that can serve as test cases for climate model evaluation. The meteorological categories are established by applying an objective k-means clustering algorithm to 11 years of standard surface-meteorological observations collected from 1 January 2000 to 31 December 2010 at the North Slope of Alaska (NSA) site of the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM). Four meteorological categories emerge. These meteorological categories constitute the first classification by meteorological regime of a long time series of Arctic meteorological conditions. The synoptic-scale patterns associated with each category, which include well-known synoptic features such as the Aleutian low and Beaufort Sea high, are used to explain the conditions at the NSA site. Cloud properties, which are not used as inputs to the k-means clustering, are found to differ significantly between the regimes and are also well explained by the synoptic-scale influences in each regime. Since the data available at the ARM NSA site include a wealth of cloud observations, this classification is well suited for model–observation comparison studies. Each category comprises an ensemble of test cases covering a representative range in variables describing atmospheric structure, moisture content, and cloud properties. This classification is offered as a complement to standard case-study evaluation of climate model parameterizations, in which models are compared against limited realizations of the Earth–atmosphere system (e.g., from detailed aircraft measurements).

Welfare Use in Japan: Trends and Determinants

2007 ◽  
pp. 88
Author(s):  
Wataru Suzuki ◽  
Yanfei Zhou
Keyword(s):  
Time Series ◽  
Longitudinal Data ◽  
Time Series Data ◽  
Positive Impact ◽  
Series Data ◽  
Negative Effects ◽  
Long Time ◽  
Welfare Use ◽  
The Impact

This article represents the first step in filling a large gap in knowledge concerning why Public Assistance (PA) use recently rose so fast in Japan. Specifically, we try to address this problem not only by performing a Blanchard and Quah decomposition on long-term monthly time series data (1960:04-2006:10), but also by estimating prefecturelevel longitudinal data. Two interesting findings emerge from the time series analysis. The first is that permanent shock imposes a continuously positive impact on the PA rate and is the main driving factor behind the recent increase in welfare use. The second finding is that the impact of temporary shock will last for a long time. The rate of the use of welfare is quite rigid because even if the PA rate rises due to temporary shocks, it takes about 8 or 9 years for it to regain its normal level. On the other hand, estimations of prefecture-level longitudinal data indicate that the Financial Capability Index (FCI) of the local government2 and minimum wage both impose negative effects on the PA rate. We also find that the rapid aging of Japan's population presents a permanent shock in practice, which makes it the most prominent contribution to surging welfare use.

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