Living Standards Measurement Survey 2003 (Wave 2 Panel) - Albania

Geographic coverage
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National

Analysis unit
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- Households
- Individuals

Kind of data
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Sample survey data [ssd]

Sampling procedure
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Sample size is 2,155 households

LSMS Sample Design

The LSMS design consisted of an equal-probability sample of housing units (HUs) within each of 16 explicit strata. These were selected in two stages. The first was to select - within strata - an agreed number of enumeration units (EAs) with probability proportional to number of HUs in the EA (according to 2001 Census data). The second stage was to select 8 HUs systematically from each selected EA. (Substitutes were used where necessary to ensure that 8 households were successfully interviewed in each EA, but I shall ignore that for current purposes.) Although probabilities within strata were (approximately) equal, probabilities varied greatly between the strata. Notably, the mountain region was heavily over-represented and the Central Rural region was under-represented in the sample.

Panel Survey Sample Design

The LSMS was so-designed, partly to enable separate analysis by broad strata (e.g. separate estimates for the mountain region). Regional analysis is much less important for the panel. The sample size will in any case be considerably smaller, so some regional sample sizes would inevitably be too small to permit robust estimation. The prime objective for the panel is to enable national-level estimates with the highest possible precision. To achieve this, the sample was structured in a way that minimises the overall variation in households' selection probabilities. In other words, the sample distribution over strata matched as closely as possible the population distribution.

- Statistical precision for national estimates is greatly improved, compared with the LSMS design. Design effects (under the assumption of equal stratum population variances) can be expected to be around 1.02 for the panel sample, compared with 1.28 for the LSMS sample. In other words, a panel sample of 1500 interviews would give precision equivalent to an equal-probability sample of 1172 households if it followed the LSMS distribution of households over strata, but gives precision equivalent to an equal-probability sample of 1471 households with the panel design. Precision is also further improved by retaining all 450 EAs in the sample, thus reducing the design effect due to the clustering (as mean responding sample size per cluster will reduce from 8.0 to around 3.3);
- The design was simple to implement as, within each stratum, the number of households to select was the same in each EA. (Note that sampling fractions have been expressed as a fraction of 8 for this reason);
- The sample size was set so as to make it likely that the number of achieved interviews would be between 1600 and 1700. Substitute households were not be used in the case of non-response.
Rather, all attempts were made to maximise the response rate. This enables the use of potentially powerful non-response weighting using the LSMS data.

Panel design

The Albanian panel survey sample was selected from households interviewed on the 2002 LSMS conducted by INSTAT with support from the World Bank. The sample size for the panel took approximately half the LSMS households and has re-interviewed these households annually in each of 2003 and 2004. The LSMS data collected in 2002 therefore constitute 'Wave 1' of the panel survey and giving three waves of panel data altogether. The fieldwork for Wave 3 was carried out in the spring of 2004.

The sample selected from the LSMS for the panel was designed to provide a nationally representative sample of households and individuals within Albania (see Appendix B for full description of the sample design and selection procedure). This differs from the LSMS where the sample was designed to be representative of each strata which broadly represented the main regions in Albania so that regional level statistics could be generated (Mountain, Central, Coastal, Tirana).

The panel also has no over-sampling as in the LSMS. This design was adopted as the smaller sample size for the panel would have made it more difficult to produce regionally representative samples and increased sampling error while over-sampling can introduce additional complications for analysis in the context of a panel. The panel data can be used for analysis broken down by strata to assess any differences between areas but should not be used to produce cross-sectional estimates at the regional level. The relatively small sample size for the panel must always be considered as cell sizes which are small have higher levels of error and can produce estimates which are less reliable. Panel surveys have a number of elements of which data users need to be aware when carrying out their analysis. The main features of the panel design are as follows:
- All members of Wave 1 households were designated as original sample members (OSMs) including children aged under 15 years.
- New members living with an OSM become eligible for inclusion in the sample
- All sample members are followed as they move address and any new members found to be living in their household included
- Sample members moving out of Albania are considered to be out of scope for that year of the survey (note that they remain potentially eligible for interview and it is possible they may return to a sample household at a future wave)
- From Wave 2, only household members aged 15 years and over are eligible for interview. As children turn 15, they become eligible for interview (This differs from the LSMS where the individual questionnaire collected some data on children under 15 from the mother or main carer).

The panel is essentially an individual level survey as individuals are followed over time regardless of the household they are living in at a given interview point. This is the key element of the panel design. Households change in composition over time as members move in and out, children are born and others die. New households are formed as people marry or children leave the parental home and households can disappear if all members die or all members move in different directions. The fact that households do not remain constant over time means that it is only possible to follow individuals over time, observing them in their household context at each interview point.

It should also be noted that a 'household' is not equivalent to a current address. A household may move to a new address but maintain the same composition. Similarly, an individual sample member may move between several addresses during the life of the survey. In this design, there is no substitution or recruitment of new households moving into addresses vacated by sample members.

Mode of data collection
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Face-to-face [f2f]

Research instrument
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Panel questionnaire content

The data for Wave 1 of the panel survey are the LSMS data so contains all the modules carried for the LSMS. To minimise respondent burden and help maintain response rates in the panel survey it was necessary to reduce the length and complexity of the LSMS questionnaire. However, it was also important to maintain comparability in question wording and response categories wherever possible as only variables which are comparable over time can be used for longitudinal analysis. The Wave 2 questionnaire is therefore a reduced version of the LSMS questionnaire with some additional elements that were required for the panel e.g. collecting details of people moving into and out of the household, and some new elements that had not been included on the LSMS. A cross-wave list of variables for Waves 1 and 2 shows which variables have been carried at both waves, which were carried at Wave 1 only and which at Wave 2 only (see ‘Variable Reconciliation LSMS_PANEL_final). The most notable changes were that the LSMS detailed consumption module was not collected at Wave 2 and the agriculture module was a reduced form compared to the LSMS.

The Wave 2 individual questionnaire contains some routing depending on whether or not the person is an original sample member interviewed on the LSMS or a new person who had joined the household since Wave 1. This is because some information only needs to be collected once e.g. place of birth and other information only needs to be updated on an annual basis. For example all qualifications were collected on the LSMS so for original members we only need to know if they have gained any new qualifications in the past year but for new members we need to ask about all qualifications. Users of the data need to be aware of this routing and in some cases may need to get information from an earlier wave if it was not collected at the current wave. Users are recommended to use the data in conjunction with the questionnaires so they are aware of the routing for different sample members.

地理覆盖范围
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- 国家级
分析单元
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- 家庭
- 个人
数据类型
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样本调查数据 [ssd]
抽样程序
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样本量为2,155个家庭
LSMS样本设计
LSMS的设计旨在包含16个明确分层中的每个分层内的住房单元（HUs）的等概率样本。这些分层通过两个阶段进行选择。第一阶段是在分层内选择具有与EA中住房单元数量成比例的概率的预定的枚举单位（EAs）。第二阶段是从每个选定的EA中系统地选择8个HUs。在必要时使用替代品以确保每个EA中成功采访到8个家庭（但在此目的下我将忽略这一点）。尽管分层内的概率（大约）相等，但不同分层之间的概率差异很大。值得注意的是，山区在样本中过度代表，而中部农村地区代表性不足。

横断面调查样本设计
LSMS的设计部分是为了能够按广泛分层（例如，对山区进行单独估计）进行单独分析。对于横断面来说，区域分析的重要性要小得多。无论如何，样本量将大大减小，因此一些区域的样本量不可避免地太小，无法进行稳健的估计。横断面的主要目标是实现尽可能高的精度进行国家级估计。为此，样本被构建成尽可能最小化家庭选择概率的整体变异。换句话说，样本在分层上的分布尽可能接近人口分布。

- 与LSMS设计相比，国家级估计的统计精度得到了显著提高。在假设分层人口方差相等的情况下，预计横断面样本的设计效应将为1.02，而LSMS样本的设计效应为1.28。换句话说，如果横断面样本为1500次访谈，其精度相当于遵循LSMS在分层上家庭分布的等概率样本1172个家庭，但如果采用横断面设计，则相当于等概率样本1471个家庭的精度。通过保留所有450个EA在样本中，也进一步提高了精度，从而减少了由于聚类引起的设计效应（因为每个聚类的平均响应样本量将从8.0减少到大约3.3）；
- 设计易于实施，因为在每个分层内，每个EA中要选择的家庭数量相同（请注意，由于这个原因，抽样比例已表示为8的分数）；
- 样本量设定得使其很可能达到1600至1700次访谈。在非响应的情况下不使用替代家庭。相反，所有努力都旨在最大化响应率。这使得可以使用LSMS数据进行潜在的强大非响应加权；

横断面设计
阿尔巴尼亚横断面调查样本是从由INSTAT进行并由世界银行支持的2002年LSMS中采访的家庭中选出的。横断面样本量大约是LSMS家庭的一半，并在2003年和2004年每年重新采访这些家庭。因此，2002年收集的LSMS数据构成了横断面调查的“第1波”，总共有三波横断面数据。第3波的实地调查于2004年春季进行。

从LSMS中为横断面选择的样本旨在为阿尔巴尼亚的家庭和个人提供全国代表性样本（参见附录B中关于样本设计和选择程序的完整描述）。这与LSMS不同，其中样本设计旨在代表每个分层，这些分层大致代表了阿尔巴尼亚的主要地区，以便生成区域级统计数据（山区、中部、沿海、地拉那）。

横断面也没有像LSMS那样的过度抽样。采用这种设计是因为横断面较小的样本量将使产生区域代表性样本变得更加困难，并增加抽样误差，而过度抽样会在横断面分析的背景下引入额外的复杂性。横断面数据可以用于按分层进行分析，以评估不同地区之间的差异，但不应用于产生区域层面的横断面估计。必须始终考虑横断面相对较小的样本量，因为单元格大小较小具有更高的误差水平，并可能产生不太可靠的估计。在进行分析时，数据使用者需要注意横断面调查的多个要素。横断面设计的特征如下：
- 第1波的 households的所有成员均被指定为原始样本成员（OSMs），包括15岁以下的儿童。
- 与OSM同住的新成员有资格加入样本
- 跟踪所有样本成员，无论他们在特定访谈点居住在哪个家庭中，以及任何发现居住在他们的家庭中的新成员
- 移出阿尔巴尼亚的样本成员被视为该调查年度的范围之外（请注意，他们仍然可能具有接受采访的资格，并且将来某个波次他们可能返回到样本家庭中）
- 从第2波开始，只有15岁及以上的家庭成员有资格接受采访。随着儿童长大，他们有资格接受采访（这与LSMS不同，其中个人问卷从母亲或主要照顾者那里收集了一些15岁以下儿童的数据）。

横断面本质上是一个个体层面的调查，因为无论个体在特定访谈点居住在哪个家庭中，都会随时间跟踪个体。这是横断面设计的核心要素。随着时间的推移，家庭组成会发生变化，因为成员的进出，孩子的出生和死亡。当人们结婚或孩子离开父母家时，会形成新的家庭。如果所有成员都死亡或所有成员都向不同的方向移动，家庭可能会消失。由于家庭不会随着时间的推移而保持不变，因此只能跟踪个体随时间的变化，在每次访谈点观察他们在家庭环境中的情况。

还应注意的是，'家庭'并不等同于当前地址。家庭可能搬到新的地址，但保持相同的组成。同样，个体样本成员在调查的生命周期中可能在不同地址之间移动。在这个设计中，没有替代或招募进入样本成员留下的地址的新家庭。

数据收集方式
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面对面 [f2f]
研究工具
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横断面问卷内容
横断面调查第1波的数据是LSMS数据，因此包含了为LSMS进行的所有模块。为了最小化受访者的负担并帮助保持横断面调查的响应率，有必要减少LSMS问卷的长度和复杂性。然而，在尽可能的情况下，也必须保持问题措辞和响应类别的可比性，因为只有随时间可比的变量才能用于纵向分析。因此，第2波的问卷是LSMS问卷的缩减版，包含了一些为横断面所需的新元素，以及一些在LSMS中没有包含的新元素。1和2波的交叉波变量列表显示了哪些变量在两个波次中都有，哪些只在第1波中，哪些只在第2波中（参见‘Variable Reconciliation LSMS_PANEL_final’）。最显著的变化是，LSMS详细的消费模块在第2波没有收集，与LSMS相比，农业模块是一种简化的形式。

第2波的个体问卷包含一些路由，取决于该人是否是在LSMS上采访的原始样本成员，或者自第1波以来加入家庭的新的个人。这是因为某些信息只需要收集一次，例如出生地和其他信息只需要每年更新一次。例如，所有资格都在LSMS上收集，因此对于原始成员，我们只需要知道他们在过去一年中是否获得了任何新的资格，但对于新成员，我们需要询问所有资格。数据使用者需要了解这种路由，在某些情况下可能需要从较早的波次获取信息，如果当前波次没有收集到这些信息。建议数据使用者将数据与问卷结合使用，以便了解不同样本成员的路由。