Replication Data for: Making International Organizations Work: The Politics of Institutional Performance (doi:10.7910/DVN/LJBKNA)

View:

Part 1: Document Description
Part 2: Study Description
Part 3: Data Files Description
Entire Codebook

Document Description

Citation

Title:

Replication Data for: Making International Organizations Work: The Politics of Institutional Performance

Identification Number:

doi:10.7910/DVN/LJBKNA

Distributor:

Harvard Dataverse

Date of Distribution:

2019-12-10

Version:

1

Bibliographic Citation:

Lall, Ranjit, 2019, "Replication Data for: Making International Organizations Work: The Politics of Institutional Performance", https://doi.org/10.7910/DVN/LJBKNA, Harvard Dataverse, V1, UNF:6:ReSldxMO2w1J8TXfIdCVYQ== [fileUNF]

Study Description

Citation

Title:

Replication Data for: Making International Organizations Work: The Politics of Institutional Performance

Identification Number:

doi:10.7910/DVN/LJBKNA

Authoring Entity:

Lall, Ranjit (Harvard University)

Producer:

Department of Government

Distributor:

Harvard Dataverse

Distributor:

Department of Government

Access Authority:

Wall, Tom

Depositor:

Lall, Ranjit

Date of Deposit:

2017-12-15

Holdings Information:

https://doi.org/10.7910/DVN/LJBKNA

Study Scope

Keywords:

Social Sciences, international organizations

Topic Classification:

Harvard University, Department of Government

Abstract:

International organizations (IOs) have emerged in recent decades as among the most important and influential actors in world politics. Surprisingly, however, we continue to know little about their performance – that is, the extent to which they achieve their objectives and do so in a manner that is cost-effective and responsive to a wide range of public and private stakeholders. This dissertation seeks to address two key questions: Why do some IOs tend to perform better than others? And what are the consequences of such differences?<br /><br /> The first part of the study explores the sources of variation in IO performance. I argue that the primary obstacle to effective performance is not opportunistic behavior by IO officials – as implied by conventional “rogue-agency” analyses – but the propensity of states to use IOs to advance narrow national interests at the expense of broader organizational goals. The implication is that IOs that enjoy policy autonomy vis-à-vis states will exhibit higher levels of performance. Critically, however, I posit that in the international context policy autonomy cannot be guaranteed by institutional design. Instead, it is a function of (1) the existence of operational alliances between IOs and actors above and below the state; and (2) the technical complexity of IO activities. I provide evidence for the argument by constructing and analyzing the first quantitative dataset on IO performance – based in part on a new wave of government evaluations of IOs and in part on an original survey of IO staff – and by conducting a comparative case study in the area of global food security. <br /><br /> The second part of the dissertation examines how variation in performance affects two significant characteristics of IOs, namely, their level of funding and accountability. I develop a theoretical framework that highlights how different aspects of the relationship between IOs and other actors within their policy space mediate the impact of such variation. Two aspects of this relationship are particularly important: (1) the degree of competition IOs face from institutions that exercise similar functions to them; and (2) the robustness of operational alliances between IOs and nonstate actors. Similarly to before, I test the argument using a mixed-methods approach, combining qualitative evidence from extensive interviews and other sources with a series of observational and quasi-experimental statistical analyses based on original panel data on organizational funding and accountability mechanisms.<br /><br /> In sum, the dissertation addresses a significant gap in the international relations literature by offering a systematic theoretical and empirical examination of the politics of IO performance. In doing so, it contributes to several strands of research on IOs – including those on institutional design, delegation, autonomy, nonstate actors, and accountability – as well as to broader ongoing debates about institutions, power, information, and change in world politics.

Unit of Analysis:

international organizations

Methodology and Processing

Sources Statement

Notes:

This study was deposited under the of the Data-PASS standard deposit terms. A copy of the usage agreement is included in the file section of this study.

Data Access

Restrictions:

<b>The data archived in the Harvard Government Dissertation Dataverse are restricted for use for five years post deposit date.</b> I will use these data solely for the purposes stated in my application to use data, detailed in a written research proposal.

Citation Requirement:

I will include a bibliographic citation acknowledging the use of these data in any publication or presentation in which these data are used. Such citations will appear in footnotes or in the reference section of any such manuscript. I understand the guideline in "How to Cite This Dataset" described in the Summary of this study.

Conditions:

The data are available without additional conditions other than those stated in the "Restrictions" Terms of Use above.

Notes:

This dataset is made available under a Creative Commons CC0 license with the following additional/modified terms and conditions:

Embargoed for 5 years from the publication date.

Other Study Description Materials

Related Publications

Citation

Title:

Lall, Ranjit. 2017. Making International Organizations Work: The Politics of Institutional Performance. Dissertation, Harvard University.

Bibliographic Citation:

Lall, Ranjit. 2017. Making International Organizations Work: The Politics of Institutional Performance. Dissertation, Harvard University.

File Description--f3091970

File: chapter2_dataset.tab

  • Number of cases: 53

  • No. of variables per record: 41

  • Type of File: text/tab-separated-values

Notes:

UNF:6:JyJRgCe6JdlArAJCwsXJOw==

File Description--f3091973

File: chapter3_dataset1.tab

  • Number of cases: 432

  • No. of variables per record: 107

  • Type of File: text/tab-separated-values

Notes:

UNF:6:GWjRj/XrYJdDdzmiu1tHgQ==

File Description--f3091972

File: chapter3_dataset2.tab

  • Number of cases: 160

  • No. of variables per record: 12

  • Type of File: text/tab-separated-values

Notes:

UNF:6:rqfWnZ7yzZrLwTnzLt3aKQ==

File Description--f3091971

File: chapter4_dataset.tab

  • Number of cases: 2195

  • No. of variables per record: 107

  • Type of File: text/tab-separated-values

Notes:

UNF:6:9Ts5nM6TmdsPUedv1dnOnw==