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Titlebook: Legislatures and the Budget Process; The Myth of Fiscal C Joachim Wehner Book 2010 Palgrave Macmillan, a division of Macmillan Publishers L

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Institutional Foundations of Legislative Control,institutional elements that determine legislative control of public spending. This synthesis is important because the effect of one institutional feature may be balanced or neutralised by another (Scartascini and Stein 2009). Hence, a highly selective analysis may lead to unrealistic expectations ab
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Assessing the Power of the Purse,espite this widespread formal recognition, the actual budgetary role of national legislatures apparently differs sharply across countries. Members of the US Congress ‘have long seen themselves as the bulwark against [executive] oppression’ and their ‘major weapon’ is the constitutional requirement f
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Legislative Institutions and Fiscal Policy Outcomes,ince the 1990s, a number of studies, using different variables and datasets, have claimed that certain institutional features are conducive to maintaining fiscal discipline during the budget process in the legislature. This chapter provides an overview of the theoretical and empirical literature on
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The Promise of Top-Down Budgeting, process and produce a prudent budget at the same time. For those who believe that elected assemblies should play an active role in budgeting, a legislative pro-spending bias may simply represent the cost of democracy, but this is unsatisfactory for those concerned with fiscal management. Can this t
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Intercontinental Transport of Trace Substances from Boreal Forest Fires,r but are transported on regional and even hemispheric scales, and they lead to radiative forcing and modify tropospheric and stratospheric chemistry..Recently, due to strong burning events in Canada and Siberia, boreal forest fires have attracted scientific interest; as for the last decades the mai
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Lightweight and Efficient Attention-Based Superresolution Generative Adversarial Networksorks, this paper optimizes the generator and discriminator based on the SRGAN model. First, the residual dense block is used as the basic structural unit of the generator to improve the network‘s feature extraction capability. Second, enhanced lightweight coordinate attention is incorporated to help
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